U.S. patent application number 14/640717 was filed with the patent office on 2015-09-10 for methods and systems for converged networking and storage.
The applicant listed for this patent is Datawise Systems, Inc.. Invention is credited to Jeffrey Chou, Kevin Fong, Jayasenan Sundara Ganesh, Amitava Guha, Gopal Sharma.
Application Number | 20150254088 14/640717 |
Document ID | / |
Family ID | 54017456 |
Filed Date | 2015-09-10 |
United States Patent
Application |
20150254088 |
Kind Code |
A1 |
Chou; Jeffrey ; et
al. |
September 10, 2015 |
METHODS AND SYSTEMS FOR CONVERGED NETWORKING AND STORAGE
Abstract
A device includes a converged input/output controller that
includes a physical target storage media controller, a physical
network interface controller and a gateway between the storage
media controller and the network interface controller, wherein
gateway provides a direct connection for storage traffic and
network traffic between the storage media controller and the
network interface controller.
Inventors: |
Chou; Jeffrey; (Palo Alto,
CA) ; Sharma; Gopal; (San Jose, CA) ; Guha;
Amitava; (San Jose, CA) ; Fong; Kevin; (Las
Vegas, NV) ; Ganesh; Jayasenan Sundara; (Cupertino,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Datawise Systems, Inc. |
San Jose |
CA |
US |
|
|
Family ID: |
54017456 |
Appl. No.: |
14/640717 |
Filed: |
March 6, 2015 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61950036 |
Mar 8, 2014 |
|
|
|
62017257 |
Jun 26, 2014 |
|
|
|
Current U.S.
Class: |
709/212 ;
711/112; 718/1 |
Current CPC
Class: |
G06F 3/061 20130101;
G06F 13/1642 20130101; G06F 3/0664 20130101; H04L 67/1002 20130101;
G06F 9/45541 20130101; G06F 3/067 20130101; H04L 67/1097
20130101 |
International
Class: |
G06F 9/455 20060101
G06F009/455; G06F 9/50 20060101 G06F009/50; H04L 29/08 20060101
H04L029/08 |
Claims
1. A device, comprising: a converged input/output controller that
includes: a physical target storage media controller, a physical
network interface controller; and a gateway between the storage
media controller and the network interface controller, wherein
gateway provides a direct connection for storage traffic and
network traffic between the storage media controller and the
network interface controller.
2. A device of claim 1, further comprising a virtual storage
interface that presents storage media controlled by the storage
media controller as locally attached storage, regardless of the
location of the storage media.
3. A device of claim 1, further comprising a virtual storage
interface that presents storage media controlled by the storage
media controller as locally attached storage, regardless of the
number or type of the storage media.
4. A device of claim 1, further comprising a virtual storage
interface that facilitates dynamic provisioning of the storage
media, wherein the physical storage may be either local or
remote.
5. A device of claim 1, further comprising a virtual network
interface that facilitates dynamic provisioning of the storage
media, wherein the physical storage may be either local or
remote.
6. A device of claim 1, wherein the device is adapted to be
installed as a controller card on a host computing system.
7. A device of claim 6, wherein the gateway operates without
intervention by the operating system, by a hypervisor, or by other
software running on the CPU of the host computing system.
8. A device of claim 1, wherein the device includes at least one of
a field programmable gate array, an ASIC, and a network processor
that provides at least one of the storage functions and the network
functions of the device.
9. A device of claim 1, wherein the device is configured as a
network-deployed switch.
10. A device of claim 1, further comprising a functional component
of the device for translating storage media instructions between a
first protocol and at least one other protocol.
11. A method of virtualization of a storage device, comprising:
accessing a physical storage device that responds to instructions
in a first storage protocol; translating instructions between the
first storage protocol and a second storage protocol; and using the
second protocol, presenting the physical storage device to an
operating system, such that the storage of the physical storage
device can be dynamically provisioned, whether the physical storage
device is local or remote to a host computing system that uses the
operating system.
12. A method of claim 11, wherein the first protocol is at least
one of a SATA protocol, an NVME protocol, a SAS protocol, an iSCSI
protocol, a fiber channel protocol and a fiber channel over
Ethernet protocol.
13. A method of claim 11, wherein the second protocol is an NVMe
protocol.
14. A method of claim 11, further comprising providing an interface
between an operating system and a device that performs the
translation of instructions between the first and second storage
protocols.
15. A method of claim 11, further comprising providing an NVMe over
Ethernet connection between the device that performs the
translation of instructions and a remote, network-deployed storage
device.
16. A method of facilitating migration of at least one of an
application, a container, and data stored on a target physical
storage device, comprising: providing a converged storage and
networking controller, wherein a gateway provides a connection for
network and storage traffic between a storage component and a
networking component of the device without requiring intervention
of the operating system, a hypervisor, or other software running on
the CPU of a host computer; and mapping the at least one
application or container to a target physical storage device that
is controlled by the converged storage and networking controller,
such that the application or container can access the target
physical storage, without requiring intervention of the operating
system, a hypervisor, or software running on the CPU of the host
system to which the target physical storage is attached, when the
application, the container, or the data stored on the target
physical storage device is moved to one or more other computing
systems.
17. A method of claim 16, wherein migration is of a Linux
container.
18. A method of claim 16, wherein migration is of a Virtual Machine
running in a hypervisor.
19. A method of claim 16, wherein the migration is of a scaleout
application.
20. A method of claim 16, wherein the target physical storage is a
network-deployed storage device that uses at least one of an iSCSI
protocol, a fiber channel protocol and a fiber channel over
Ethernet protocol.
21. A method of claim 16, wherein the target physical storage is a
direct attached storage device that uses at least one of a SAS
protocol, a SATA protocol and an NVME protocol.
22. A method of providing quality of service (QoS) for a network,
comprising: providing a converged storage and networking
controller, wherein a gateway provides a connection for network and
storage traffic between a storage component and a networking
component of the device without intervention of the operating
system, a hypervisor, or software running on the CPU of the host
computer; and without intervention of the operating system of a
host computer, managing at least one quality of service (QoS)
parameter related to a network in the data path of which the
storage and networking controller is deployed, such managing being
based on at least one of the storage traffic and the network
traffic that is handled by the converged storage and networking
controller.
23. A method of claim 22, wherein the QoS parameter is selected
from the group consisting of a bandwidth parameter, a network
latency parameter, an IO performance parameter, a throughput
parameter, a storage type parameter and a storage latency
parameter.
24. A method of claim 22, wherein the QoS is maintained
automatically when at least one of an application and a container
that is serviced by storage through the converged storage and
network controller is migrated from a host computer to another
computer.
25. A method of claim 22, wherein the QoS is maintained
automatically when at least one target storage device that services
at least one of an application and a container through the
converged storage and network controller is migrated from a first
location to at least one second location.
26. A method of claim 22, wherein a security feature is selected
from the group consisting of encryption of network traffic data,
encryption of data in storage, and encryption of network traffic
data and data in storage.
27. A method of claim 22, wherein one or more storage features is
provided, the storage feature selected from the group consisting of
compression, protection levels, RAID levels, storage media type,
global de-duplication, and snapshot intervals for achieving at
least one of a recovery point objective (RPO) and a recovery time
objective (RTO).
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to the following
provisional applications, each of which is incorporated herein by
reference in its entirety: U.S. patent application 61/950,036,
filed Mar. 8, 2014 and entitled "Method and Apparatus for
Application Driven Storage Access"; and U.S. patent application
62/017,257, filed Jun. 26, 2014 and entitled "Apparatus for
Virtualized Cluster IO".
FIELD OF THE INVENTION
[0002] This application relates to the fields of networking and
data storage, and more particularly to the field of converged
networking and data storage devices.
BACKGROUND OF THE INVENTION
[0003] The proliferation of scale-out applications has led to very
significant challenges for enterprises that use such applications.
Enterprises typically choose between solutions like virtual
machines (involving software components like hypervisors and
premium hardware components) and so-called "bare metal" solutions
(typically involving use of an operating system like Linux.TM. and
commodity hardware. At large scale, virtual machine solutions
typically have poor input-output (IO) performance, inadequate
memory, inconsistent performance, and high infrastructure cost.
Bare metal solutions typically have static resource allocation
(making changes in resources difficult and resulting in inefficient
use of the hardware), challenges in planning capacity, inconsistent
performance, and operational complexity. In both cases,
inconsistent performance characterizes the existing solutions. A
need exists for solutions that provide high performance in
multi-tenant deployments, that can handle dynamic resource
allocation, and that can use commodity hardware with a high degree
of utilization.
[0004] FIG. 1 depicts the general architecture of a computing
system 102, such as a server, functions and modules of which may be
involved in certain embodiments disclosed herein. Storage functions
(such as access to local storage devices on the server 102, such as
media 104 (e.g., rotating media or flash) and network functions
such as forwarding have traditionally been performed separately in
either software stacks or hardware devices (e.g., involving a
network interface controller 118 or a storage controller 112, for
network functions or storage functions, respectively). Within an
operating system stack 108 (which may include an operating system
and a hypervisor in some embodiments including all the software
stacks associated with storage and networking functions for the
computing system), the software storage stack typically includes
modules enabling use of various protocols that can be used in
storage, such as the small computer system interface (SCSI)
protocol, the serial ATA (SATA) protocol, the non-volatile memory
express (NVMe) protocol (a protocol for accessing disk-attached
storage (DAS), like solid-state drives (SSDs), through the PCI
Express (PCIe) bus 110 of a typical computing system 102) or the
like. The PCIe bus 110 may provide an interconnection between a CPU
106 (with processor(s) and memory) and various IO cards. The
storage stack also may include volume managers, etc. Operations
within the storage software stack may also include data protection,
such as mirroring or RAID, backup, snapshots, deduplication,
compression and encryption. Some of the storage functions may be
offloaded into a storage controller 112. The software network stack
includes modules, functions and the like for enabling use of
various networking protocols, such as Transmission Control
Protocol/Internet Protocol (TCP/IP), the domain name system
protocol (DNS), the address resolution protocol (ARP), forwarding
protocols, and the like. Some of the network functions may be
offloaded into a network interface controller 118 (or NIC) or the
network fabric switch, such as via an ethernet connection 120, in
turn leading to a network (with various switches, routers and the
like). In virtualized environments, a NIC 118 may be virtualized
into several virtual NICs as specified by SR-IOV under the PCI
Express standard. Although not specified by the PCI Express
standard and not as common, storage controllers can also be
virtualized in a similar manner. This approach allows virtual
entities, such as virtual machines, access to their own private
resource.
[0005] Referring to FIG. 2, one major problem with hypervisors is
with the complexity of IO operations. For example, in order to deal
with an operation involving data across two different computers
(computer system 1 and computer system 2 in FIG. 2), data must be
copied repeatedly, over and over, as it moves among the different
software stacks involved in local storage devices 104, storage
controllers 112, the CPUs 106, network interface controller 118 and
the hypervisor/operating systems 108 of the computers, resulting in
large numbers of inefficient data copies for each IO operation
whenever an activity is undertaken that involves moving data from
one computer to another, changing the configuration of storage, or
the like. The route 124 is one of many examples of the complex
routes that data may take from one computer to another, moving up
and down the software stacks of the two computers. Data that is
sought by computing system 2 may be initially located in a local
storage device 104, such as a disk, of computing system 1, then
pulled by a storage controller card 112 (involving an IO operation
and copying), send over the PCIe bus 110 (another IO operation) to
the CPU 108 where it is handled by a hypervisor or other software
component of the OS stack 108 of computing system 1. Next, the data
may be delivered (another IO operation) through the network
controller 118 and over the network 122 (another set of IO
operations) to computing system 2. The route continues on computing
system 2, where data may travel through the network controller 118
and to the CPU 106 of computing system 2 (involve additional IO
operations), then sent over the PCIe bus 110 to the local storage
controller 112 for storage, then back to the hypervisor/OS stack
108 for actual use. These operations may occur across a
multiplicity of pairs of computing systems, with each exchange
involving this kind of proliferation of IO operations (and many
other routes are possible, each involving significant numbers of
operations). Many such complex data replication and transport
activities among computing systems are required in scaleout
situations, which are increasingly adopted by enterprises. For
example, when implementing a scaleout application like MongoDB.TM.,
customers must repeatedly run real time queries during rebalancing
operations, and perform large scale data loading. Such activities
involve very large numbers of IO operations, which result in poor
performance in hypervisor solutions. Users of those applications
also frequently re-shard (change the shards on which data is
deployed), resulting in big problems for bare metal solutions that
have static storage resource allocations, as migration of data from
one location to another also involves many copying and transport
operations, with large numbers of IO operations. As the amount of
data used in scaleout applications grows rapidly, and the
connectedness among disparate systems increases (such as in cloud
deployments involving many machines), these problems grow
exponentially. A need exists for storage and networking solutions
that reduce the number and complexity of IO operations and
otherwise improve the performance and scaleability of scaleout
applications without requiring expensive, premium hardware.
[0006] Referring still to FIG. 2, for many applications and use
cases, data (and in turn, storage) needs to be accessed across the
network between computing systems 102. Three high-level steps of
this operation include the transfer of data from the storage media
of one computing system out of a box, movement across the network
122, and the transfer of data into a second box (second computing
system 102) to the storage media 104 of that second computing
system 102. First, out of the box transfer, may involve
intervention from the storage controller 112, the storage stack in
the OS 108, the network stack in the OS 108, and the network
interface controller 118. Many traversals and copying across
internal busses (PCIe 110 and memory) as well as CPU 106 processing
cycles are spent. This not only degrades performance (creating
latency and throughput issues) of the operation, but also adversely
affects other applications that run on the CPU. Second, once the
data leaves the box, 102 and moves onto the network 122, it is
treated like any other network traffic and needs to be
forwarded/routed to its destination. Policies are executed and
decisions are made. In environments where a large amount of traffic
is moving, congestion can occur in the network 122, causing
degradation in performance as well as problems with availability
(e.g., dropped packets, lost connections, and unpredictable
latencies). Networks have mechanisms and algorithms to avoid
spreading of congestion, such as pause functions, backward
congestion notification (BCN), explicit congestion notification
(ECN), etc. However, these are reactive methods; that is, they
detect formation of congestion points and push back on the source
to reduce congestion, potentially resulting in delays and
performance impacts. Third, once the data arrives at its
"destination" computing system 102, it needs to be processed, which
involves intervention from the network interface controller 118,
the network stack in the OS 108, the storage stack in the OS 108,
and the storage controller 112. As with out of the box operations
noted above, many traversals and copying across internal busses as
well as CPU 106 processing cycles are spent. Further, the final
destination of the data may well reside in still a different box.
This can be the result of a need for more data protection (e.g.,
mirroring or across-box RAID) or the need for de-duplication. If
so, then the entire sequence of out-of-the box, across the network,
and into the box data transfer needs to be repeated again. As
described, limitations of this approach include degradation in raw
performance, unpredictable performance, impact on other tenants or
operations, availability and reliability, and inefficient use of
resources. A need exists for data transfer systems that avoid the
complexity and performance impacts of the current approaches.
[0007] As an alternative to hypervisors (which provide a separate
operating system for each virtual machine that they manage),
technologies such as Linux.TM. containers have been developed
(which enable a single operating system to manage multiple
application containers). Also, tools such as Dockers have been
developed, which provide provisioning for packaging applications
with libraries. Among many other innovations described throughout
this disclosure, an opportunity exists for leveraging the
capabilities of these emerging technologies to provide improved
methods and systems for scaleout applications.
SUMMARY
[0008] Provided herein are methods and systems that include a
converged storage and network controller in hardware that combines
initiator, target storage functions and network functions into a
single data and control path, which allows a "cut-through" path
between the network and storage, without requiring intervention by
a host CPU. For ease of reference, this is referred to variously in
this disclosure as a converged hardware solution, a converged
device, a converged adaptor, a converged IO controller, a
"datawise" controller, or the like throughout this disclosure, and
such terms should be understood to encompass, except where context
indicates otherwise, a converged storage and network controller in
hardware that combines target storage functions and network
functions into a single data and control path.
[0009] Among other benefits, the converged solution will increase
raw performance of a cluster of computing and/or storage resources;
enforce service level agreements (SLAs) across the cluster and help
guarantee predictable performance; provide a multi-tenant
environment where a tenant will not affect its neighbor, provide a
denser cluster with higher utilization of the hardware resulting in
smaller data center footprint, less power, fewer systems to manage;
provide a more scalable cluster, and pool storage resources across
the cluster without loss of performance.
[0010] The various methods and systems disclosed herein provide
high-density consolidation of resources required for scaleout
applications and high performance multi-node pooling. These methods
and systems provide a number of customer benefits, including
dynamic cluster-wide resource provisioning, the ability to
guarantee quality-of-service (QoS), Security, Isolation etc. on
network and storage functions, and the ability to use shared
infrastructure for production and testing/development.
[0011] Also provided herein are methods and systems to perform
storage functions through the network and to virtualize storage and
network devices for high performance and deterministic performance
in single or multi-tenant environments.
[0012] Also provided herein are methods and systems for
virtualization of storage devices, such as those using NVMe and
similar protocols, and the translation of those virtual devices to
different physical devices, such as ones using SATA.
[0013] The methods and systems disclosed herein also include
methods and systems for end-to-end congestion control involving
only the hardware on the host (as opposed to the network fabric)
that includes remote credit management and a distributed scheduling
algorithm at the box level.
[0014] Also provided herein are various methods and systems that
are enabled by the converged network/storage controller, including
methods and systems for virtualization of a storage cluster or of
other elements that enable a cluster, such as a storage adaptor, a
network adaptor, a container (e.g., a Linux container), a Solaris
zone or the like. Among advantages, one aspect of virtualizing a
cluster is that containers can become location-independent in the
physical cluster. Among other advantages, this allows movement of
containers among machines in a vastly simplified process described
below.
[0015] Provided herein are methods and systems for virtualizing
direct-attached storage (DAS), so that the operating system stack
108 still sees a local, persistent device, even if the physical
storage is moved and is remotely located; that is, provided herein
are methods and systems for virtualization of DAS. In embodiments
this may include virtualizing DAS over a fabric, that is, taking a
DAS storage system and moving it outside the box and putting it on
the network. In embodiments this may include carving DAS into
arbitrary name spaces. In embodiments the virtualized DAS is made
accessible as if it were actual DAS to the operating system, such
as being accessible by the OS 108 over a PCIe bus via NVMe. Thus,
provided herein is the ability to virtualize storage (including
DAS) so that the OS 108 sees it as DAS, even if the storage is
actually accessed over a network protocol such as Ethernet, and the
OS 108 is not required to do anything different than would be
required with local physical storage.
[0016] Provided herein are methods and systems for providing DAS
across a fabric, including exposing virtualized DAS to the OS 108
without requiring any modification of the OS 108.
[0017] Also provided herein are methods and systems for
virtualization of a storage adaptor (referring to a target storage
system).
[0018] Provided herein are methods and systems for combining
storage initiation and storage targeting in a single hardware
system. In embodiments, these may be attached by a PCIe bus 110. A
single root virtualization function (SR-IOV) may be applied to take
any standard device and have it act as if it is hundreds of such
devices. Embodiments disclosed herein include using SR-IOV to give
multiple virtual instances of a physical storage adaptor. SR-IOV is
a PCIe standard that virtualizes I/O functions, and while it has
been used for network interfaces, the methods and systems disclosed
herein extend it to use for storage devices. Thus, provided herein
is a virtual target storage system.
[0019] Embodiments may include a switch form factor or network
interface controller, wherein the methods and systems disclosed
herein may include a host agent (either in software or hardware).
Embodiments may include breaking up virtualization between a front
end and a back end.
[0020] Embodiments may include various points of deployment for a
converged network and target storage controller. While some
embodiments locate the converged device on a host computing system
102, in other cases the disk can be moved to another box (e.g.,
connected by Ethernet to a switch that switches among various boxes
below. While a layer may be needed to virtualize, the storage can
be separated, so that one can scale storage and computing resources
separately. Also, one can then enable blade servers (i.e.,
stateless servers). Installations that would have formerly involved
expensive blade servers and attached to storage area networks
(SANs) can instead attach to the switch. In embodiments this
comprises a "rackscale" architecture where resources are
disaggregated at the rack level.
[0021] Methods and systems disclosed herein include methods and
systems for virtualizing various types of non-DAS storage as DAS in
a converged networking/target storage appliance. In embodiments,
one may virtualize whatever storage is desired as DAS, using
various front end protocols to the storage systems while exposing
storage as DAS to the OS stack 108.
[0022] Methods and systems disclosed herein include virtualization
of a converged network/storage adaptor. From a traffic perspective,
one may combine systems into one. Combining the storage and network
adaptors, and adding in virtualization, gives significant
advantages. Say there is a single host 102 with two PCIe buses 110.
To route from the PCIe 110, you can use a system like RDMA to get
to another machine/host 102. If one were to do this separately, one
has to configure the storage and the network RDMA system
separately. One has to join each one and configure them at two
different places. In the converged scenario, the whole step of
setting up QoS, seeing that this is RDMA and that there is another
fabric elsewhere is a zero touch process, because with combined
storage and networking the two can be configured in a single step.
That is, once one knows the storage, one doesn't need to set up the
QoS on the network separately.
[0023] Method and systems disclosed herein include virtualization
and/or indirection of networking and storage functions, embodied in
the hardware, optionally in a converged network adaptor/storage
adaptor appliance. While virtualization is a level of indirection,
protocol is another level of indirection. The methods and systems
disclosed herein may convert a protocol suitable for use by most
operating systems to deal with local storage, such as NVMe, to
another protocol, such as SAS, SATA, or the like. One may expose a
consistent interface to the OS 108, such as NVMe, and in the back
end one may convert to whatever storage media is cost-effective.
This gives a user a price/performance advantage. If components are
cheaper/faster, one can connect any one of them. The back end could
be anything, including NVMe.
[0024] Provided herein are methods and systems that include a
converged data path for network and storage functions in an
appliance. Alternative embodiments may provide a converged data
path for network and storage functions in a switch.
[0025] In embodiments, methods and systems disclosed herein include
storage/network tunneling, wherein the tunneling path between
storage systems over a network does not involve the operating
system of a source or target computer. In conventional systems, one
had separate storage and network paths, so accessing storage
remotely, required extensive copying to and from memory, I/O buses,
etc. Merging the two paths means that storage traffic is going
straight onto the network. The OS 108 of each computer sees only a
local disk. Another advantage is simplicity of programming. A user
does not need to separately program a SAN, meaning that the methods
disclosed herein include a one-step programmable SAN. Rather than
requiring discovery and specification of zones, and the like,
encryption, attachment, detachment and the like may be centrally,
and programmatically done.
[0026] Embodiments disclosed herein may include virtualizing the
storage to the OS 108 so that the OS 108 sees storage as a local
disk. The level of indirection involved in the methods and systems
disclosed herein allows the converged system to hide not only the
location, but the media type, of storage media. All the OS sees is
that there is a local disk, even if the actual storage is located
remotely and/or is or a different type, such as a SAN. Thus,
virtualization of storage is provided, where the OS 108 and
applications do not have to change. One can hide all of the
management, policies of tiering, polices of backup, policies of
protection and the like that are normally needed to configure
complex storage types behind.
[0027] Methods and systems are provided for selecting where
indirection occurs in the virtualization of storage. Virtualization
of certain functions may occur in hardware (e.g., in an adaptor on
a host, in a switch, and in varying form factors (e.g., FPGA or
ASICs) and in software. Different topologies are available, such as
where the methods and systems disclosed herein are deployed on a
host machine, on a top of the rack switch, or in a combination
thereof. Factors that go into the selection include ease of use.
Users who want to run stateless servers may prefer a top of rack.
Ones who don't care about that approach might prefer the controller
on the host.
[0028] Methods and systems disclosed herein include providing NVMe
over Ethernet. These approaches can be the basis for the tunneling
protocol that is used between devices. NVMe is a suitable DAS
protocol that is intended conventionally to go to a local PCIe.
Embodiments disclosed herein may tunnel the NVMe protocol traffic
over Ethernet. NVMe (non-volatile memory express) is a protocol
that in Linux and Windows provides access to PCIe-based Flash
Storage. This provides high performance by by-passing the software
stacks used in conventional systems.
[0029] Embodiments disclosed herein may include providing an NVMe
device that is virtualized and dynamically allocated. In
embodiments one may piggy back NVMe, but carve up and virtualize
and dynamically allocate an NVMe device. In embodiments there is no
footprint in the software. The operating system stays the same
(just a small driver that sees the converged network/storage card).
This results in virtual storage presented like a direct attached
disk, but the difference is that now we can pool such devices
across the network.
[0030] Provided herein are methods and systems for providing the
simplicity of direct attached storage (DAS) with the advantages of
sharing like in a storage area network (SAN). Each converged
appliance in various embodiments disclosed herein may be a host,
and any storage drives may be local to a particular host but seen
by the other hosts (as in a SAN or other network-accessible
storage). The drives in each box enabled by a network/storage
controller of the present disclosure behave like a SAN (that is,
are available on the network), but the management methods are much
simpler. When a storage administrator sets up a SAN, a typical
enterprise may have a whole department setting up zones for a SAN
(e.g., a fiber channel switch), such as setting up "who sees what."
That knowledge is pre-loaded and a user has to ask the SAN
administrator to do the work to set it up. There is no
programmability in a typical legacy SAN architecture. The methods
and systems disclosed herein provide local units that are on the
network, but the local units can still access their storage without
having to go through complex management steps like zone definition,
etc. These devices can do what a SAN does just by having both
network and storage awareness. As such, they represent the first
programmatic SAN.
[0031] Methods and systems disclosed herein may include persistent,
stateful, disaggregated storage enabled by a hardware appliance
that provides converged network and storage data management.
[0032] Methods and systems disclosed herein may also include
convergence of network and storage data management in a single
appliance, adapted to support use of containers for virtualization.
Such methods and systems are compatible with the container
ecosystem that is emerging, but offering certain additional
advantages.
[0033] Methods and systems are disclosed herein for implementing
virtualization of NVMe. Regardless how many sources to how many
destinations, as long as the data from the sources is serialized
first before going into the hub, then the hub distributes to data
to the designated destination sequentially. If so, then data
transport resources such as DMA engine can be reduced to only one
copy. This may include various use scenarios. In one scenario, for
NVMe virtual functions (VFs), if they are all connected to the same
PCIe bus, then regardless how many VFs are configured, the data
would be coming into this pool of VFs serially, so there is only
one DMA engine and only one storage block (for control information)
is needed. In another use scenario, for a disk storage system with
a pool of discrete disks/controllers, if the data is originated
from the physical bus, i.e. PCIe, since the data is serially coming
into this pool of disks, then regardless how many disks/controllers
are in the pool, the transport resources such as the DMA engine can
be reduced to only one instead of one per controller.
[0034] In accordance with various exemplary and non-limiting
embodiments, a device comprises a converged input/output controller
that includes a physical target storage media controller, a
physical network interface controller; and a gateway between the
storage media controller and the network interface controller,
wherein gateway provides a direct connection for storage traffic
and network traffic between the storage media controller and the
network interface controller.
[0035] In accordance with various exemplary and non-limiting
embodiments, a method of virtualization of a storage device
comprises accessing a physical storage device that responds to
instructions in a first storage protocol, translating instructions
between the first storage protocol and a second storage protocol
and using the second protocol, presenting the physical storage
device to an operating system, such that the storage of the
physical storage device can be dynamically provisioned, whether the
physical storage device is local or remote to a host computing
system that uses the operating system.
[0036] In accordance with various exemplary and non-limiting
embodiments, a method of facilitating migration of at least one of
an application and a container comprises providing a converged
storage and networking controller, wherein a gateway provides a
connection for network and storage traffic between a storage
component and a networking component of the device without
intervention of the operating system of a host computer and mapping
the at least one application or container to a target physical
storage device that is controlled by the converged storage and
networking controller, such that the application or container can
access the target physical storage, without intervention of the
operating system of the host system to which the target physical
storage is attached, when the application or container is moved to
another computing system.
[0037] In accordance with various exemplary and non-limiting
embodiments, a method of providing quality of service (QoS) for a
network, comprises providing a converged storage and networking
controller, wherein a gateway provides a connection for network and
storage traffic between a storage component and a networking
component of the device without intervention of the operating
system, a hypervisor, or other software running on the CPU of a
host computer and, also without intervention of the operating
system, hypervisor, or other software running on the CPU of a host
computer, managing at least one quality of service (QoS) parameter
related to a network in the data path of which the storage and
networking controller is deployed, such managing being based on at
least one of the storage traffic and the network traffic that is
handled by the converged storage and networking controller.
[0038] QoS may be based on various parameters, such as one or more
of a bandwidth parameter, a network latency parameter, an IO
performance parameter, a throughput parameter, a storage type
parameter and a storage latency parameter. QoS may be maintained
automatically when at least one of an application and a container
that is serviced by storage through the converged storage and
network controller is migrated from a host computer to another
computer. Similarly, QoS may be maintained automatically when at
least one target storage device that services at least one of an
application and a container through the converged storage and
network controller is migrated from a first location to another
location or multiple locations. For example, storage may be scaled,
or different storage media types may be selected, to meet storage
needs as requirements are increased. In embodiments, a security
feature may be provided, such as encryption of network traffic
data, encryption of data in storage, or both. Various storage
features may be provided as well, such as compression, protection
levels (e.g., RAID levels), use of different storage media types,
global de-duplication, and snapshot intervals for achieving at
least one of a recovery point objective (RPO) and a recovery time
objective (RTO).
BRIEF DESCRIPTION OF THE FIGURES
[0039] The accompanying figures where like reference numerals refer
to identical or functionally similar elements throughout the
separate views and which together with the detailed description
below are incorporated in and form part of the specification, serve
to further illustrate various embodiments and to explain various
principles and advantages all in accordance with the systems and
methods disclosed herein.
[0040] FIG. 1 illustrates a general architecture in accordance with
an exemplary and non-limiting embodiment.
[0041] FIG. 2 illustrates a computer system in accordance with an
exemplary and non-limiting embodiment.
[0042] FIG. 3 illustrates a converged solution in accordance with
an exemplary and non-limiting embodiment.
[0043] FIG. 4 illustrates two computing systems enabled by a
converged solution in accordance with an exemplary and non-limiting
embodiment.
[0044] FIG. 5 illustrates a converged controller in accordance with
an exemplary and non-limiting embodiment.
[0045] FIG. 6 illustrates a deployment of a converged controller in
accordance with an exemplary and non-limiting embodiment.
[0046] FIG. 7 illustrates a plurality of systems in accordance with
an exemplary and non-limiting embodiment.
[0047] FIG. 8 illustrates a block diagram of a field-programmable
gate array (FPGA) in accordance with an exemplary and non-limiting
embodiment.
[0048] FIG. 9 illustrates an architecture of a controller card in
accordance with an exemplary and non-limiting embodiment.
[0049] FIG. 10 illustrates a software stack in accordance with an
exemplary and non-limiting embodiment.
[0050] FIGS. 11-15 illustrate the movement of an application
container across multiple systems in accordance with an exemplary
and non-limiting embodiment.
[0051] FIG. 16 illustrates packet transmission in accordance with
an exemplary and non-limiting embodiment.
[0052] FIG. 17 illustrates a storage access scheme in accordance
with an exemplary and non-limiting embodiment.
[0053] FIG. 18 illustrates the operation of a file system in
accordance with an exemplary and non-limiting embodiment.
[0054] FIG. 19 illustrates the operation of a distributed file
server in accordance with an exemplary and non-limiting
embodiment.
[0055] FIG. 20 illustrates a high performance distributed file
server (DFS) in accordance with an exemplary and non-limiting
embodiment.
[0056] FIG. 21 illustrates a system in accordance with an exemplary
and non-limiting embodiment.
[0057] FIG. 22 illustrates a host in accordance with an exemplary
and non-limiting embodiment.
[0058] FIG. 23 illustrates an application accessing a block of data
in accordance with an exemplary and non-limiting embodiment.
[0059] FIG. 24 illustrates an application accessing a block of data
in accordance with an exemplary and non-limiting embodiment.
[0060] FIG. 25 illustrates a system in accordance with an exemplary
and non-limiting embodiment.
[0061] FIG. 26 illustrates a method according to an exemplary and
non-limiting embodiment.
[0062] FIG. 27 illustrates a method according to an exemplary and
non-limiting embodiment.
[0063] FIG. 28 illustrates a method according to an exemplary and
non-limiting embodiment.
[0064] Skilled artisans will appreciate that elements in the
figures are illustrated for simplicity and clarity and have not
necessarily been drawn to scale. For example, the dimensions of
some of the elements in the figures may be exaggerated relative to
other elements to help to improve understanding of embodiments of
the systems and methods disclosed herein.
DETAILED DESCRIPTION OF THE INVENTION
[0065] The present disclosure will now be described in detail by
describing various illustrative, non-limiting embodiments thereof
with reference to the accompanying drawings and exhibits. The
disclosure may, however, be embodied in many different forms and
should not be construed as being limited to the illustrative
embodiments set forth herein. Rather, the embodiments are provided
so that this disclosure will be thorough and will fully convey the
concept of the disclosure to those skilled in the art. The claims
should be consulted to ascertain the true scope of the
disclosure.
[0066] Before describing in detail embodiments that are in
accordance with the systems and methods disclosed herein, it should
be observed that the embodiments reside primarily in combinations
of method steps and/or system components related to converged
networking and storage. Accordingly, the system components and
method steps have been represented where appropriate by
conventional symbols in the drawings, showing only those specific
details that are pertinent to understanding the embodiments of the
systems and methods disclosed herein so as not to obscure the
disclosure with details that will be readily apparent to those of
ordinary skill in the art.
[0067] Referring to FIG. 3, the converged solution 300 may include
three important aspects and may be implemented in a hardware device
that includes a combination of hardware and software modules and
functions. First, a cut-through data path 304 may be provided
between a network controller 118 and a storage controller 112, so
that access of the storage to and from the network can be direct,
without requiring any intervention of the OS stack 108, the PCIe
bus 110, or the CPU 106. Second, cut through storage stack access,
such as to storage devices 302, may be provided, such as access of
the storage to and from entities on the local host, which allows
bypassing of complex legacy software stacks for storage access,
such as SCSI/SAS/SATA stacks. Third, end-to-end congestion
management and flow control of the network may be provided, such as
by a mechanism to reserve and schedule the transfer of data across
the network, which guarantees the availability of the target's data
to remote initiators and minimizes the congestion of the traffic as
it flows through intermediate network fabric switches. The first
and second aspects remove software stacks (hence the CPU 106 and
memory) from the path of the data, eliminating redundant or
unnecessary movement and processing. End-to-end congestion
management and flow control delivers a deterministic and reliable
transport of the data.
[0068] As noted above, one benefit of the converged solution 300 is
that the operating system stack 108 connects to the converged
solution 300 over a conventional PCIe 110 or a similar bus, so that
the OS stack 108 sees the converged solution 300, and any storage
that it controls through the cut-through to storage devices 302, as
one or more local, persistent devices, even if the physical storage
is remotely located. Among other things, this comprises the
capability for virtualization of DAS 308, which may include
virtualizing DAS 308 over a fabric, that is, taking a DAS 308
storage system and moving it outside the computing system 102 and
putting it on the network. The storage controller 112 of the
converged solution 300 may connect to and control DAS 308 on the
network 122 via various known protocols, such as SAS, SATA, or
NVMe. In embodiments virtualization may include carving DAS 308
into arbitrary name spaces. In embodiments the virtualized DAS 308
is made accessible as if it were actual, local, physical DAS to the
operating system, such as being accessible by the OS 108 over a
PCIe bus 110 to the storage controller 112 of the converged
solution 300 via a standard protocol such as NVMe. Again, the OS
108 sees the entire solution 300 as a local, physical device, such
as DAS. Thus, provided herein is the ability to virtualize storage
(including DAS and other storage types, such as SAN 310) so that
the OS 108 sees any storage type as DAS, even if the storage is
actually accessed over a network 122, and the OS 108 is not
required to do anything different than would be required with local
physical storage. In the case where the storage devices 302 are SAN
310 storage, the storage controller 112 of the converged solution
may control the SAN 310 through an appropriate protocol used for
storage area networks, such as the Internet Small Computing System
Interface (iSCSI), Fibre Channel (FC), or Fibre Channel over
Ethernet (FCoE). Thus, the converged solution 300 provides a
translation for the OS stack 108 from any of the other protocols
used in storage, such as Ethernet, SAS, SATA, NVMe, iSCSI, FC or
FCoE, among others, to a simple protocol like NVMe that makes the
disparate storage types and protocols appear as local storage
accessible over PCIe 110. This translation in turns enables
virtualization of a storage adaptor (referring to any kind of
target storage system). Thus, methods and systems disclosed herein
include methods and systems for virtualizing various types of
non-DAS storage as DAS in a converged networking/target storage
appliance 300. In embodiments, one may virtualize whatever storage
is desired as DAS, using various protocols to the storage systems
while exposing storage as DAS to the OS stack 108. Thus, provided
herein are methods and systems for virtualization of storage
devices, such as those using NVMe and similar protocols, and the
translation of those virtual devices to different physical devices,
such as ones using SATA.
[0069] Storage/network tunneling 304, where the tunneling path
between storage systems over the network 122 does not involve the
operating system of a source or target computer enables a number of
benefits. In conventional systems, one has separate storage and
network paths, so accessing storage remotely required extensive
copying to and from memory, I/O buses, etc. Merging the two paths
means that storage traffic is going straight onto the network. An
advantage is simplicity of programming. A user does not need to
separately program a SAN 310, meaning that the methods disclosed
herein enable a one-step programmable SAN 310. Rather than
requiring discovery and specification of zones, and the like,
configuration, encryption, attachment, detachment and the like may
be centrally, and programmatically done. As an example, a typical
SAN is composed of "initiators," "targets," and a switch fabric,
which connects the initiators and targets. Typically which
initiators see which targets are defined/controlled by the fabric
switches, called "zones." Therefore, if an initiator moves or a
target moves, zones need to be updated. The second control portion
of a SAN typically lies with the "targets." They can control which
initiator port can see what logical unit numbers (LUNs) (storage
units exposed by the target). This is typically referred to as LUN
masking and LUN mapping. Again, if an initiator moves locations,
one has to re-program the "Target". Consider now that in such an
environment if an application moves from one host to another (such
as due to a failover, load re-balancing, or the like) the zoning
and LUN masking/mapping needs to be updated. Alternatively, one
could pre-program the SAN, so that every initiator sees every
target. However, doing so results in an un-scalable and un-secure
SAN. In the alternate solution described throughout this
disclosure, such a movement of an application, a container, or a
storage device does NOT require any SAN re-programming, resulting
in a zero touch solution. The mapping maintained and executed by
the converged solution 300 allows an application or a container,
the target storage media, or both, to be moved (including to
multiple locations) and scaled independently, without intervention
by the OS, a hypervisor, or other software running on the host
CPU.
[0070] The fact that the OS 108 sees storage as a local disk allows
simplified virtualization of storage. The level of indirection
involved in the methods and systems disclosed herein allows the
converged system 300 to hide not only the location, but the media
type, of storage media. All the OS 108 sees is that there is a
local disk, even if the actual storage is located remotely and/or
is or a different type, such as a SAN 310. Thus, virtualization of
storage is provided through the converged solution 300, where the
OS 108 and applications do not have to change. One can hide all of
the management, policies of tiering, polices of backup, policies of
protection and the like that are normally needed to configure
complex storage types behind.
[0071] The converged solution 300 enables the simplicity of direct
attached storage (DAS) with the advantages of a storage area
network (SAN). Each converged appliance 300 in various embodiments
disclosed herein may act as a host, and any storage devices 302 may
be local to a particular host but seen by the other hosts (as is
the case in a SAN 310 or other network-accessible storage). The
drives in each box enabled by a network/storage controller of the
present disclosure behave like a SAN 310 (e.g., are available on
the network), but the management methods are much simpler. When a
storage administrator normally sets up a SAN 310, a typical
enterprise may have a whole department setting up zones for a SAN
310 (e.g., a fiber channel switch), such as setting up "who sees
what." That knowledge must be pre-loaded, and a user has to ask the
SAN 310 administrator to do the work to set it up. There is no
programmability in a typical legacy SAN 310 architecture. The
methods and systems disclosed herein provide local units that are
on the network, but the local units can still access their storage
without having to go through complex management steps like zone
definition, etc. These devices can do what a SAN does just by
having both network and storage awareness. As such, they represent
the first programmatic SAN.
[0072] The solution 300 can be described as a "Converged IO
Controller" that controls both the storage media 302 and the
network 122. This converged controller 300 is not just a simple
integration of the storage controller 112 and the network
controller (NIC) 118. The actual functions of the storage and
network are merged such that storage functions are performed as the
data traverses to and from the network interface. The functions may
be provided in a hardware solution, such as an FPGA (one or more)
or ASIC (one or more) as detailed below.
[0073] Referring to FIG. 4, two or more computing systems 102
enabled by converged solutions 300 may serve as hosts for
respective storage targets, where by merging storage and network
and controlling both interfaces, direct access to the storage 302
can be achieved remotely over the network 122 without traversing
internal busses or CPU/software work, such as by a point-to-point
path 400 or by an Ethernet switch 402 to another computer system
102 that is enabled by a converged solution 300. The highest
performance (high IOPs and low latency) can be achieved. Further,
storage resources 302 can now be pooled across the cluster. In FIG.
4, this is conceptually illustrated by the dotted oval 404.
[0074] In embodiments, the converged solution 300 may be included
on a host computing system 102, with the various components of a
conventional computing system as depicted in FIG. 1, together with
the converged IO controller 300 as described in connection with
FIG. 3. Referring to FIG. 5, in alternative embodiments, the
converged controller 300 may be disposed in a switch, such as a top
of the rack switch, thus enabling a storage enabled switch 500. The
switch may reside on the network 122 and be accessed by a network
controller 118, such as of a conventional computing system 102.
[0075] Referring to FIG. 6, systems may be deployed in which a
converged controller 300 is disposed both on one or more host
computing systems 102 and on a storage enabled switch 500, which
may be connected to systems 102 that are enabled by converged
solutions 300 and to non-enabled systems 102. As noted above,
target storage 302 for the converged controller(s) 300 on the host
computing system 102 and on the storage enabled switch 500 can be
visible to each other across the network, such as being treated as
a unified resource, such as to virtualization solutions. In sum,
intelligence, including handling converged network and storage
traffic on the same device, can be located in a host system, in a
switch, or both in various alternative embodiments of the present
disclosure.
[0076] Embodiments disclosed herein may thus include a switch form
factor or a network interface controller, or both which may include
a host agent (either in software or hardware). These varying
deployments allow breaking up virtualization capabilities, such as
on a host and/or on a switch and/or between a front end and a back
end. While a layer may be needed to virtualize certain functions,
the storage can be separated, so that one can scale storage and
computing resources separately. Also, one can then enable blade
servers (i.e., stateless servers). Installations that would have
formerly involved expensive blade servers and attached storage area
networks (SANs) can instead attach to the storage enabled switch
500. In embodiments this comprises a "rackscale" architecture,
where resources are disaggregated at the rack level.
[0077] Methods and systems are provided for selecting where
indirection occurs in the virtualization of storage. Virtualization
of certain functions may occur in hardware (e.g., in a converged
adaptor 300 on a host 102, in a storage enabled switch 500, in
varying hardware form factors (e.g., FPGAs or ASICs) and in
software. Different topologies are available, such as where the
methods and systems disclosed herein are deployed on a host machine
102, on a top of the rack switch 500, or in a combination thereof.
Factors that go into the selection of where virtualization should
occur include ease of use. Users who want to run stateless servers
may prefer a top of rack storage enabled switch 500. Ones who don't
care about that approach might prefer the converged controller 300
on the host 102.
[0078] FIG. 7 shows a more detailed view of a set of systems that
are enabled with converged controllers 300, including two computer
systems 102 (computer system 1 and computer system 2), as well as a
storage enabled switch 500. Storage devices 302, such as DAS 308
and SAN 310 may be controlled by the converged controller 300 or
the storage enabled switch 500. DAS 308 may be controlled in either
case using SAS, SATA or NVMe protocols. SAN 310 may be controlled
in either case using iSCSI, FC or FCoE. Connections among hosts 102
that have storage controllers 300 may be over a point-to-point path
400, over an Ethernet switch 402, or through a storage enabled
switch 500, which also may provide a connection to a conventional
computing system. As noted above, the multiple systems with
intelligent converged controllers 300 can each serve as hosts and
as storage target locations that the other hosts see, thereby
providing the option to be treated as a single cluster of storage
for purposes of an operating system 108 of a computing system
102.
[0079] Method and systems disclosed herein include virtualization
and/or indirection of networking and storage functions, embodied in
the hardware converged controller 300, optionally in a converged
network adaptor/storage adaptor appliance 300. While virtualization
is a level of indirection, protocol is another level of
indirection. The methods and systems disclosed herein may convert a
protocol suitable for use by most operating systems to deal with
local storage, such as NVMe, to another protocol, such as SAS,
SATA, or the like. One may expose a consistent interface to the OS
108, such as NVMe, and on the other side of the converged
controller 300 one may convert to whatever storage media 302 is
cost-effective. This gives a user a price/performance advantage. If
components are cheaper/faster, one can connect any one of them. The
side of the converged controller 300 could face any kind of
storage, including NVMe. Furthermore the storage media type may be
any of the following including, but not limited, to HDD, SSD (based
on SLC, MLC, or TLC Flash), RAM etc or a combination thereof.
[0080] In embodiments, a converged controller may be adapted to
virtualize NVMe virtual functions, and to provide access to remote
storage devices 302, such as ones connected to a storage-enabled
switch 500, via NVMe over an Ethernet switch 402. Thus, the
converged solution 300 enables the use of NVMe over Ethernet 700,
or NVMeoE. Thus, methods and systems disclosed herein include
providing NVMe over Ethernet. These approaches can be the basis for
the tunneling protocol that is used between devices, such as the
host computing system 102 enabled by a converged controller 300
and/or a storage enabled switch 500. NVMe is a suitable DAS
protocol that is intended conventionally to go to a local PCIe 110.
Embodiments disclosed herein may tunnel the NVMe protocol traffic
over Ethernet. NVMe (non-volatile memory express) is a protocol
that in Linux and Windows provides access to PCIe-based Flash. This
provides high performance via by-passing the software stacks used
in conventional systems, while avoiding the need to translate from
NVMe (as used by the OS stack 108) and the traffic tunneled over
Ethernet to other devices.
[0081] FIG. 8 is a block diagram of an FPGA 800, which may reside
on an IO controller card and enable an embodiment of a converged
solution 300. Note that while a single FPGA 800 is depicted, the
various functional blocks could be organized into multiple FPGAs,
into one or more customer Application Specific Integrated Circuits
(ASICs), or the like. For example, various networking blocks and
various storage blocks could be handled in separate (but
interconnected) FPGAs or ASICs. References throughout this
disclosure to an FPGA 800 should be understood, except where
context indicates otherwise, to encompass these other forms of
hardware that can enable the functional capabilities reflected in
FIG. 8 and similar functions. Also, certain functional groups, such
as for networking functions and/or storage functions, could be
embodied in merchant silicon.
[0082] The embodiment of the FPGA 800 of FIG. 8 has four main
interfaces. First, there is PCIe interface, such as to the PCIe bus
110 of a host computer 102. Thus, the card is a PCIe end point.
Second, there is a DRAM/NVRAM interface. For example, a DDR
interface may be provided to external DRAM or NVRAM, used by the
embedded CPUs, meta-data and data structures, and packet/data
buffering. Third, there is a storage interface to media, such as
DAS 308 and SAN 310. Storage interfaces can include ones for SAS,
SATA, NVMe, iSCSI, FC and/or FCoE, and could in embodiments be any
interface to rotating media, flash, or other persistent form of
storage, either local or over a cut-through to a network-enabled
storage like SAN 310. Fourth, a network interface is provided, such
as Ethernet to a network fabric. The storage interfaces and the
network interfaces can be used, in part, to enable NVMe over
Ethernet.
[0083] The internal functions of the FPGA 800 may include a number
of enabling features for the converged solution 300 and other
aspects of the present disclosure noted throughout. A set of
virtual endpoints (vNVMe) 802 may be provided for the host.
Analogous to the SR-IOV protocol that is used for the network
interface, this presents virtual storage targets to the host. In
this embodiment of the FPGA 800, NVMe has benefits of low software
overhead, which in turn provides high performance. A virtual NVMe
device 802 can be dynamically allocated/de-allocated/moved and
resized. As with SR-IOV, there is one physical function (PF) 806
that interfaces with a PCIe driver 110 (see below), and multiple
virtual functions 807 (VF) in which each appears as an NVMe
device.
[0084] Also provided in the FPGA 802 functions are one or more read
and write direct memory access (DMA) queues 804, referred to in
some cases herein as a DMA engine 804. These may include interrupt
queues, doorbells, and other standard functions to perform DMA to
and from the host computing system 102.
[0085] A device mapping facility 808 on the FPGA 800 may determine
the location of the virtual NVMe devices 802. The location options
would be local (ie--attached to one of the storage media interfaces
824 shown), or remote on another host 102 of a storage controller
300. Access to a remote vNVMe device requires going through a
tunnel 828 to the network 122.
[0086] A NVMe virtualization facility 810 may translate NVMe
protocol instructions and operations to the corresponding protocol
and operations of the backend storage media 302, such as SAS or
SATA (in the case of use of NVMe on the backend storage medium 302,
no translation may be needed) where DAS 308 is used, or such as
iSCSI, FC or FCoE in the case where SAN 310 storage is used in the
backend. References to the backend here refer to the other side of
the converged controller 300 from the host 102.
[0087] A data transformation function 812 may format the data as it
is stored onto the storage media 302. These operations could
include re-writes, transformation, compression, protection (such as
RAID), encryption and other functions that involve changing the
format of the data in any way as necessary to allow it to be
handled by the applicable type of target storage medium 308. In
some embodiments, storage medium 308 may be remote.
[0088] In embodiments, storage read and write queues 814 may
include data structures or buffering for staging data during a
transfer. In embodiments, temporary memory, such as DRAM of NVRAM
(which may be located off the FPGA 800) may be used for temporary
storage of data.
[0089] A local storage scheduler and shaper 818 may prioritize and
control access to the storage media 302. Any applicable SLA
policies for local storage may be enforced in the scheduler and
shaper 818, which may include strict priorities, weighted round
robin scheduling, IOP shapers, and policers, which may apply on a
per queue, per initiator, per target, or per c-group basis, and the
like.
[0090] A data placement facility 820 may implement an algorithm
that determines how the data is laid out on the storage media 302.
That may involve various placement schemes known to those of skill
in the art, such as striping across the media, localizing to a
single device 302, using a subset of the devices 302, or localizing
to particular blocks on a device 302.
[0091] A storage metadata management facility 822 may include data
structures for data placement, block and object i-nodes,
compression, deduplication, and protection. Metadata may be stored
either in off-FPGA 800 NVRAM/DRAM or in the storage media 302.
[0092] A plurality of control blocks 824 may provide the interface
to the storage media. These may include SAS, SATA, NVMe, PCIe,
iSCSI, FC and/or FCoE, among other possible control blocks, in each
case as needed for the appropriate type of target storage media
302.
[0093] A storage network tunnel 828 of the FPGA 800 may provide the
tunneling/cut-through capabilities described throughout this
disclosure in connection with the converged solution 300. Among
other things, the tunnel 828 provides the gateway between storage
traffic and network traffic. It includes
encapsulation/de-encapsulation or the storage traffic, rewrite and
formatting of the data, and end-to-end coordination of the transfer
of data. The coordination may be between FPGAs 800 across nodes
within a host computing system 102 or in more than one computing
system 102, such as for the point-to-point path 404 described in
connection with FIG. 4. Various functions, such as sequence
numbers, packet loss, time-outs, and retransmissions may be
performed. Tunneling may occur over Ethernet, including by FCoE or
NVMeoE.
[0094] A virtual network interface card facility 830 may include a
plurality of SR-IOV endpoints to the host 102, presented as virtual
network interface cards. One physical function (PF) 836 may
interfaces with a PCIe driver 110 (see software description below),
and multiple virtual functions (VF) 837, in which each appear as a
network interface card (NIC) 118.
[0095] A set of receive/transmit DMA queues 832 may include
interrupt queues, doorbells, and other standard functions to
perform DMA to and from the host 102.
[0096] A classifier and flow management facility 834 may perform
standard network traffic classification, typically to IEEE standard
802.1Q class of service (COS) mappings or other priority
levels.
[0097] An access control and rewrite facility 838 may handle access
control lists (ACLs) and rewrite policies, including access control
lists typically operating on Ethernet tuples (MAC SA/DA, IP SA/DA,
TCP ports, etc.) to reclassify or rewrite packets.
[0098] A forwarding function 840 may determines destination of the
packet, such as through layer 2 (L2) or layer 3 (L3)
mechanisms.
[0099] A set of network receive and transmit queues 842 may handle
data structures or buffering to the network interface. Off-FPGA 800
DRAM may be used for packet data.
[0100] A network/remote storage scheduler and policer 844 may
provide priorities and control access to the network interface. SLA
policies for remote storage and network traffic may be enforced
here, which may include strict priorities, weighted round robin,
IOP and bandwidth shapers, and policers on a per queue, per
initiator, per target, per c-group, or per network flow basis, and
the like.
[0101] A local network switch 848 may forward packets between
queues in the FPGA, so that traffic does not need to exit the FPGA
800 to the network fabric 122 if the destination is local to the
FPGA 800 or the host 102.
[0102] An end-to-end congestion control/credit facility 850 may
prevent network congestion. This is accomplished with two
algorithms. First there may be an end-to-end reservation/credit
mechanism with a remote FPGA 800. This may be analogous to a SCSI
transfer ready function, where the remote FPGA 800 permits the
storage transfer if it can immediately accept the data. Similarly,
the local FPGA 800 allocates credits to remote FPGAs 800 as they
request a transfer. SLA policies for remote storage may also be
enforced here. Second there may be a distributed scheduling
algorithm, such as an iterative round-robin algorithm, such as the
iSLIP algorithm for input-queues proposed in the publication "The
iSLIP Scheduling Algorithm for Input-Queues Switches", by Nick
McKeown, IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 7, NO. 2, APRIL
1999. The algorithm may be performed cluster wide using the
intermediate network fabric as the crossbar.
[0103] A rewrite, tag, and CRC facility 852 may
encapsulate/de-encapulate the packet with the appropriate tags and
CRC protection.
[0104] A set of interfaces 854, such as MAC interfaces, may provide
an interface to Ethernet.
[0105] A set of embedded CPU and cache complexes 858 may implement
a process control plan, exception handling, and other communication
to and from the local host and network remote FPGAs 800.
[0106] A memory controller 860, such as a DDR controller, may act
as a controller for the external DRAM/NVRAM.
[0107] As a result of the integration of functions provided by the
converged solution 300, as embodied in one example by the FPGA 800,
provided herein are methods and systems for combining storage
initiation and storage targeting in a single hardware system. In
embodiments, these may be attached by a PCIe bus 110. A single root
virtualization function (SR-IOV) or the like may be applied to take
any standard device (e.g., any storage media 302 device) and have
it act as if it is hundreds of such devices. Embodiments disclosed
herein include using a protocol like SR-IOV to give multiple
virtual instances of a physical storage adaptor. SR-IOV is a PCIe
standard that virtualizes I/O functions, and while it has been used
for network interfaces, the methods and systems disclosed herein
extend it to use for storage devices. Thus, provided herein is a
virtualized target storage system. In embodiments the virtual
target storage system may handle disparate media as if the media
are a disk or disks, such as DAS 310.
[0108] Enabled by embodiments like the FPGA 800, embodiments of the
methods and systems disclosed herein may also include providing an
NVMe device that is virtualized and dynamically allocated. In
embodiments one may piggyback the normal NVMe protocol, but carve
up, virtualize and dynamically allocate the NVMe device. In
embodiments there is no footprint in the software. The operating
system 108 stays the same or nearly the same (possibly having a
small driver that sees the converged network/storage card 300).
This results in virtual storage that looks like a direct attached
disk, but the difference is that now we can pool such storage
devices 302 across the network 122.
[0109] Methods and systems are disclosed herein for implementing
virtualization of NVMe. Regardless how many sources are related to
how many destinations, as long as the data from the sources is
serialized first before going into the hub, then the hub
distributes to data to the designated destination sequentially. If
so, then data transport resources such as the DMA queues 804, 832
can be reduced to only one copy. This may include various use
scenarios. In one scenario, for NVMe virtual functions (VFs), if
they are all connected to the same PCIe bus 110, then regardless
how many VFs 807 are configured, the data would be coming into this
pool of VFs 807 serially, so there is only one DMA engine 804, and
only one storage block (for control information) is needed.
[0110] In another use scenario, for a disk storage system with a
pool of discrete disks/controllers, if the data is originated from
the physical bus, i.e. PCIe 110, since the data is serially coming
into this pool of disks, then regardless how many disks/controllers
are in the pool, the transport resources such as the DMA engine 804
can be reduced to only one instead of one per controller.
[0111] Methods and systems disclosed herein may also include
virtualization of a converged network/storage adaptor 300. From a
traffic perspective, one may combine systems into one. Combining
the storage and network adaptors, and adding in virtualization,
gives significant advantages. Say there is a single host 102 with
two PCIe buses 110. To route from the PCIe 110, you can use a
system like remote direct memory access (RDMA) to get to another
machine/host 102. If one were to do this separately, one has to
configure the storage and the network RDMA systems separately. One
has to join each one and configure them at two different places. In
the converged solution 300, the whole step of setting up QoS,
seeing that this is RDMA and that there is another fabric elsewhere
is a zero touch process, because with combined storage and
networking the two can be configured in a single step. That is,
once one knows the storage, one doesn't need to set up the QoS on
the network separately. Thus, single-step configuration of network
and storage for RDMA solutions is enabled by the converged solution
300.
[0112] Referring again to FIG. 4, remote access is enabled by the
FPGA 800 or similar hardware as described in connection with FIG.
8. The virtualization boundary is indicated in FIG. 4 by the dotted
line 408. To the left of this line, virtual storage devices (e.g.,
NVMe 802) and virtual network interfaces 830 are presented to the
operating system 108. The operating system cannot tell these are
virtual devices. To the right of the virtualization boundary 408
are physical storage devices 302 (e.g., using SATA or other
protocols noted above) and physical network interfaces. Storage
virtualization functions are implemented by the vNVMe 802 and the
NVMe virtualization facility 810 of FIG. 8. Network virtualization
functions are implemented by the vNIC facility 830. Location of the
physical storage media is also hidden from the operating system
108. Effectively, the physical disks 302 across servers can be
pooled and accessed remotely. The operating system 108 issues a
read or write transaction to the storage media 302 (it is a virtual
device, but the operation system 108 sees it as a physical device).
If the physical storage media 302 happens to be remote, the
read/write transaction is mapped to the proper physical location,
encapsulated, and tunneled through Ethernet. This process may be
implemented by the device mapping facility 808, the NVMe
virtualization facility 810, the data transformation facility 812
and the storage-network tunnel 828 of FIG. 8. The target server
(second computing system) un-tunnels the storage read/write and
directly accesses its local storage media 302. If the transaction
is a write, the data is written to the media 302. If the
transaction is a read, the data is prepared, mapped to the origin
server, encapsulated, and tunneled through Ethernet. The
transaction completion arrives at the origin operating system 102.
In a conventional system, these steps would require software
intervention in order to process the storage request, data
formatting, and network access. As shown, all of these complex
software steps are avoided.
[0113] Referring to FIG. 9, a simplified block diagram is provided
of an architecture of a controller card 902, as one embodiment of a
converged solution 300 as described throughout this disclosure. The
controller card 902 may be, for example, a standard, full-height,
half-length PCIe card, such as a Gen3 x16 card. However, a
non-standard card size is acceptable, preferably sized so that it
can fit into various types of targeted chassis. The PCIe form
factor limits the stack up and layers used on the PCB.
[0114] The controller card 902 may be used as an add-on card on a
commodity chassis, such as a 2RU, 4 node chassis. Each node of the
chassis (called a sled) is typically IRU and 6.76'' wide. The
motherboard typically may provide a PCIe Gen3 x16 connector near
the back. A riser card may be used to allow the Controller card 902
to be installed on top of the motherboard; thus, the clearance
between the card and the motherboard may be limited to roughly on
slot width.
[0115] In embodiments, the maximum power supplied by the PCIe
connector is 75 W. The controller card 902 may consume about 60 W
or less.
[0116] The chassis may provide good airflow, but the card should
expect a 10 C rise in ambient temperature, because in this example
the air will be warmed by dual Xeon processors and 16 DIMMs. The
maximum ambient temperature for most servers is 35 C, so the air
temperature at the controller card 902 will likely be 45 C or
higher in some situations. Custom heat sinks and baffles may be
considered as part of the thermal solution.
[0117] There are two FPGAs in the embodiment of the controller card
902 depicted in FIG. 9, a datapath FPGA, or datapath chip 904, and
a networking FPGA, or networking chip 908.
[0118] The datapath chip 904 provides connectivity to the host
computer 102 over the PCIe connector 110. From the host processor's
point of view, the controller card 902 looks like multiple NVMe
devices. The datapath chip 904 bridges NVMe to standard SATA/SAS
protocol and in this embodiment controls up to six external disk
drives over SATA/SAS links. Note that SATA supports up to 6.0 Gbps,
while SAS supports up to 12.0 Gbps.
[0119] The networking chip 908 switches the two 10G Ethernet ports
of the NIC device 118 and the eCPU 1018 to two external 10G
Ethernet ports. It also contains a large number of data structures
for used in virtualization.
[0120] The motherboard of the host 102 typically provides a PCIe
Gen3 x16 interface that can be divided into two separate PCIe Gen3
x8 busses in the Intel chipset. One of the PCIe Gen3 x8 bus 110 is
connected to the Intel NIC device 118. The second PCIe Gen3 x8 bus
110 is connected to a PLX PCIe switch chip 1010. The downstream
ports of the switch chip 1010 are configured as two PCIe Gen3 x8
busses 110. One of the busses 110 is connected to the eCPU while
the second is connected to the datapath chip 904.
[0121] The datapath chip 904 uses external memory for data storage.
A single x72 DDR3 channel 1012 should provide sufficient bandwidth
for most situations. The networking chip 908 also uses external
memory for data storage, and a single x72 DDR3 channel is likely to
be sufficient for most situations. In addition, the data structures
require the use of non-volatile memory, such as one that provides
high performance and sufficient density, such as Non-volatile DIMM
(NVDIMM, which typically has a built-in power switching circuit and
super-capacitors as energy storage elements for data retention.
[0122] The eCPU 1018 communicates with the networking 908 using two
sets of interfaces. It has a PCIe Gen2x4 interface for NVMe-like
communication. The eCPU 1018 also has two 10G Ethernet interfaces
that connect to the networking chip 908, such as through its L2
switch.
[0123] An AXI bus 1020 (a bus specification of the ARM chipset)
will be used throughout the internal design of the two chips 904,
908. To allow seamless communication between the datapath chip 904
and the networking chip 908, the AXI bus 1020 is used for
chip-to-chip connection. The Xilinx Aurora.TM. protocol, a serial
interface, may be used as the physical layer.
[0124] The key requirements for FPGA configuration are that (1) The
datapath chip 904 must be ready before PCIe configuration started
(QSPI Flash memory (serial flash memory with quad SPI bus
interface) may be fast enough) and (2) the chips are preferably
field upgradeable. The Flash memory for configuration is preferably
large enough to store at least 3 copies of the configuration
bitstream. The bitstream refers to the configuration memory pattern
used by Xilinx.TM. FPGAs. The bitstream is typically stored in
non-volatile memory and is used to configure the FPGA during
initial power-on. The eCPU 1018 may be provided with a facility to
read and write the configuration Flash memories. New bitstreams may
reside with the processor of the host 102. Security and
authentication may be handled by the eCPU 1018 before attempting to
upgrade the Flash memories.
[0125] In a networking subsystem, the Controller card 902 may
handle all network traffic between the host processor and the
outside world. The Networking chip 908 may intercept all network
traffics from the NIC 118 and externally.
[0126] The Intel NIC 118 in this embodiment connects two10GigE, XFI
interfaces 1022 to the Networking chip 908. The embedded processor
will do the same. The Networking chip 908 will perform an L2
switching function and route Ethernet traffic out to the two
external 10GigE ports. Similarly, incoming 10GigE traffic will be
directly to either the NIC 118, the eCPU 1018, or internal logic of
the Networking chip 908.
[0127] The controller card 902 may use SFP+ optical connectors for
the two external 10G Ethernet ports. In other embodiments, the card
may support 10OGBASE-T using an external PHY and RJ45 connectors;
but a separate card may be needed, or a custom paddle card
arrangement may be needed to allow switching between SFP+ and
RJ45.
[0128] All the management of the external port and optics,
including the operation of the LEDs, may be controlled by the
Networking chip 908. Thus, signals such as PRST, I2C/MDIO, etc may
be connected to the Networking chip 908 instead of the NIC 118.
[0129] In a storage subsystem, the Datapath chip 904 may drive the
mini-SAS HD connectors directly. In embodiments such as depicted in
FIG. 10, the signals may be designed to operate at 12 Gbps to
support the latest SAS standard.
[0130] To provide efficient use of board space, two x4 mini-SAS HD
connectors may be used. All eight sets of signals may be connected
to the Datapath chip 904, even though only six sets of signals
might be used at any one time.
[0131] On the chassis, high-speed copper cables may be used to
connect the mini-SAS HD connectors to the motherboard. The
placement of the mini-SAS HD connectors may take into account the
various chassis' physical space and routing of the cables.
[0132] The power to the controller card 902 may be supplied by the
PCIe x16 connector. No external power connection needs to be used.
Per PCIe specification, the PCIe x16 connector may supply only up
to 25 W of power after power up. The controller card 902 may be
designed such that it draws less than 25 W until after PCIe
configuration. Thus, a number of interfaces and components may need
to be held in reset after initial power up. The connector may
supply up to 75 W of power after configuration, which may be
arranged such that the 75 W is split between the 3.3V and 12V
rails.
[0133] FIG. 10 shows a software stack 1000, which includes a driver
1002 to interface to the converged solution 300, such as one
enabled by the FPGA 800. The NVMe controller 1004 is the set of
functions of the hardware (e.g., FPGA 800) that serves the function
of an NVMe controller and allocates virtual devices 1012 to the
host. In FIG. 10, dev1, dev2, dev3 are examples of virtual devices
1012 which are dynamically allocated to containers 1018 LXC1, LXC2,
and LXC3, respectively. The NVMe to SATA bridge 1008 is the part of
the hardware sub-system (e.g., FPGA 800) that converts and maps
virtual devices 1012 (dev1, dev2, dev3) to storage devices 302
(e.g., SSDs in the figure). The connection 1010 is the part of the
hardware system that provides a SATA connection (among other
possible connection options noted above). The Ethernet link 120,
which can expose virtual devices 1012 (i.e dev1, dev2, dev3) to
other host(s) 102 connected via the Ethernet link 120 using a
storage tunneling protocol. The PCI-E (NVMe driver) 1002 may
program and drive the hardware subsystem for the storage side. This
driver 1002 may run on the host as part of the operating system
(e.g., Linux OS in this example). The block layer 1014 may be a
conventional SCSI sub-system of the Linux operating system, which
may interface with the converged solution PCIe driver 1002 to
expose virtual storage devices 1012. The containers 1018 (LXC1,
LXC2, LXC3) may request and dynamically be allocated virtual
storage devices 1012 (dev1, dev2 and dev3, respectively).
[0134] FIGS. 11 through 15 show an example of the movement of an
application container 1018 (e.g., a Linux container) across
multiple systems 102, first in the absence of a converged solution
300 and then in the presence of such a converged solution 300. FIG.
11 shows an example of two conventional computer systems 102 with
conventional storage controllers 112 and network controllers 118
hosting virtualized software in an OS/Hypervisor stack 108.
Computer System 1 (C1) has a configuration similar to the one shown
in FIG. 1 with CPU, memory and conventional storage controller 112
and network controller 118. The system runs an operating system
108, such as Linux.TM., Microsoft Windows.TM., etc, and/or
hypervisor software, such as Xen, VMware, etc. to provide support
for multiple applications natively or over virtualized
environments, such as via virtual machines or containers. In this
computer system 102, application App1 1102 is running inside a
virtual machine VM 11104. Applications App2 1108 and App3 1112 are
running within virtualized containers LXC1 1110 and LXC2 1114
respectively. In addition to these, application App4 1118 is
running natively over the Operating System 108. Although typically,
a practical scenario might have only virtual machines or containers
or native applications (not all three), here it is depicted in a
combined fashion deliberately to cover all cases of virtualized
environments. Computer System 2 (C2) 102 has similar configuration
supporting App5 and App6 in a container and natively, respectively.
Each of these applications access their storage devices 302
independent of each other, namely App1 uses S1, App2 uses S2, etc.
These storage devices 302 (designated S1-S6) are not limited to
being independent physical entities. They could be logically carved
out of one or more physical storage elements as deemed necessary.
As one can see, (represented by the arrow from each storage device
302 to an application), the data flow between the storage 302 and
the application 1102, 1108, 1112, 1118 passes through the storage
controller 112 and the operating system/hypervisor stack 108 before
it reaches the application, entailing the challenges described in
connection with FIG. 1.
[0135] Referring to FIG. 12, when an application or a container is
moved from C1 to C2, its corresponding storage device needs to be
moved too. The movement could be needed due to the fact that C1
might be running out of resources (such as CPU, memory, etc.) to
support the existing applications (App1-App4) over a period of
time, such as because of behavioral changes within these
applications.
[0136] Typically, it is easier to accomplish the movement within a
reasonable amount of time as long as the application states and the
storage are reasonable in terms of size. Typically storage-intense
applications may use large amounts (e.g., multiple terabytes) of
storage, in which case, it may not be practical to move the storage
302 within an acceptable amount of time. In that case, storage may
continue to stay where it was and software-level shunting/tunneling
would be undertaken to access the storage remotely, as shown in
FIG. 13.
[0137] As shown in FIG. 13, App2 1108, after its movement to
computer system C2, continues to access its original storage S2
located on computer system C1 by traversing through Operating
Systems or Hypervisors 108 of both the systems C1 and C2. This is
because the mapping of storage access through the network
controllers 118 to that storage controller 112 and its attached
storage devices 302 is done by the Operating System or Hypervisor
software stack 108 running within the main CPU.
[0138] As shown in FIG. 13 after its movement to C2, App2 1108
continues to access its original storage S2 located in C1 by
traversing through Operating Systems or Hypervisors 108 of both the
systems C1 and C2. This is because, the mapping of storage access
through the network controllers 118 from C2 to C1 and over to that
storage controller 112 of C1 is done by the Operating System or
Hypervisor software 108 running within the main CPU of each
computer system.
[0139] Consider a similar scenario when a converged controller 300
is applied as shown in the FIG. 14. As one can see, the scenario is
almost identical to FIG. 11, except the Converged IO Controller 300
replaces the separate storage controller 112 and network controller
118. In this case, when App2 1108 along with its container LXC1 is
moved to C2 (as shown in FIG. 15), the storage S2 is not moved, and
the access is optimized by avoiding the traversal through any
software (Operating System, Hypervisor 108 or any other) running in
main CPU present in computing system C1.
[0140] Thus, provided herein is a novel way of bypassing the main
CPU where a storage device is located, which in turn (a) allows one
to reduce latency and bandwidth significantly in accessing a
storage across multiple computer systems and (b) vastly simplifies
and improves situations in which an application needs to be moved
away from a machine on which its storage is located.
[0141] Ethernet networks behave on a best effort basis and hence
lossy in nature as well as bursty. Any packet could be lost forever
or buffered and delivered in bursty and delayed manner along with
other packets. Whereas, typical storage centric applications are
sensitive to losses and bursts, it is important that when storage
traffic is sent over Ethernet networks.
[0142] Conventional storage accesses over their buses/networks
involve reliable and predictable methods. For example, Fibre
Channel networks employ credit based flow control to limit number
of accesses made by end systems. And the number of credits given to
an end system is based on whether the storage device has enough
command buffers to receive and fulfill storage requests in
predictable amount of time fulfilling required latency and
bandwidth needs. The figure below shows some credit schemes adopted
by different types of buses such as SATA, Fibre Channel (FC), SCSI,
SAS, etc.
[0143] Referring to FIG. 16, Ethernet networks behave on a best
effort basis and hence tend to be lossy in nature, as well as
bursty. Any packet could be lost forever or buffered and delivered
in a delayed manner, in a congestion-inducing burst, along with
many other packets. Typical storage-centric applications are
sensitive to losses and bursts, so it is important when storage
traffic is sent over buses and Ethernet networks, that those
involve reliable and predictable methods for maintaining integrity.
For example, Fibre Channel networks conventionally employ
credit-based flow control to limit the number of accesses made by
end systems at any one time. The number of credits given to an end
system can be based on whether the storage device 302 has enough
command buffers to receive and fulfill storage requests in a
predictable amount of time that satisfies required latency and
bandwidth requirements. FIG. 16 shows some of the credit schemes
adopted by different types of buses such as a SATA bus 1602, Fibre
Channel (FC) 1604, and SCSI/SAS connection 1608, among other types
of such schemes.
[0144] As one can see, for example, an FC controller 1610 may have
its own buffering up to a limit of `N` storage commands before
sending them to an FC-based storage device 1612, but the FC device
1612 might have a different buffer limit, say `M` in this example,
which could be greater than, equal to, or less than `N`. A typical
credit-based scheme uses target level (in this example, one of the
storage devices 302, such as the FC Device 1602, is the target)
aggregate credits, information about which is propagated to various
sources (in this example, the controller, such as the FC Controller
1610, is the source) which are trying to access the target 302. For
example, if two sources are accessing a target that has a queue
depth of `N,` then sum of the credits given to the sources would
not exceed `N,` so that at any given time the target will not
receive more than `N` commands. The distribution of credits among
the sources may be arbitrary, or it may be based on various types
of policies (e.g., priorities based on cost/pricing, SLAs, or the
like). When the queue is serviced, by fulfilling the command
requests, credits may be replenished at the sources as appropriate.
By adhering to this kind of credit-based storage access, losses
that would result from queues at the target being overwhelmed can
be avoided.
[0145] Typical storage accesses over Ethernet, such as FCOE, iSCSI,
and the like, may extend the target-oriented, credit-based command
fulfillment to transfers over Ethernet links. In such cases, they
may be target device-oriented, rather than being source-oriented.
Provided herein are new credit based schemes that can instead be
based on which or what kind of source should get how many credits.
For example, the converged solution 300 described above, which
directly interfaces the network to the storage, may employ a
multiplexer to map a source-oriented, credit-based scheduling
scheme to a target device oriented credit based scheme, as shown in
FIG. 17.
[0146] As shown in FIG. 17, four sources are located over Ethernet
and there are two target storage devices 302. Typical
target-oriented, credit-based schemes would expose two queues (one
per target), or two connections per source to each of the targets.
Instead, as shown in FIG. 17, the queues (Q1,Q2,Q3,Q4) 1702 are on
a per-source basis, and they mapped/multiplexed to two
target-oriented queues (Q5,Q6) 1704 across the multiplexor (S)
1708. By employing this type of source-oriented, credit-based
scheme, one may guarantee access bandwidth and predictable access
latency, independent of the number of target storage devices 302.
As an example, one type of multiplexing is to make sure queue size
`P` of Q1 does not exceed `L+M` of Q5 and Q6, so that Q1 is not
overwhelmed by its source.
[0147] In embodiments, methods and systems to provide access to
blocks of data from a storage device 302 is described. In
particular, a novel approach to allowing an application to access
its data, fulfilling a specific set of access requirements is
described.
[0148] As used herein, the term "application-driven data storage"
(ADS) encompasses storage that provides transparency to any
application in terms of how the application's data is stored,
accessed, transferred, cached and delivered to the application. ADS
may allow applications to control these individual phases to
address the specific needs of the particular application. As an
example, an application might be comprised of multiple instances of
itself, as well as multiple processes spread across multiple Linux
nodes across the network. These processes might access multiple
files in shared or exclusive manners among them. Based on how the
application wants to handle these files, these processes may want
to access different portions of the files more frequently, may need
quick accesses or use once and throw away. Based on these criteria,
it might want to prefetch and/or retain specific portions of a file
in different tiers of cache and/or storage for immediate access on
per session or per file basis as it wishes. These application
specific requirements cannot be fulfilled in a generic manner such
as disk striping of entire file system, prefetching of read-ahead
sequential blocks, reserving physical memory in the server or LRU
or FIFO based caching of file contents.
[0149] Application-driven data storage I/O is not simply applicable
to the storage entities alone. It impacts the entire storage stack
in several ways. First, it impacts the storage I/O stack in the
computing node where the application is running comprising the
Linux paging system, buffering, underlying File system client,
TCP/IP stack, classification, QoS treatment and packet queuing
provided by the networking hardware and software. Second, it
impacts the networking infrastructure that interconnects the
application node and its storage, comprising Ethernet segments,
optimal path selections, buffering in switches, classification and
QoS treatment of latency-sensitive storage traffic as well as
implosion issues related to storage I/O. Also, it impacts the
storage infrastructure which stores and maintains the data in terms
of files comprising the underlying file layout, redundancy, access
time, tiering between various types of storage as well as remote
repositories.
[0150] Methods and systems disclosed herein include ones relating
to the elements affecting a typical application within an
application node and how a converged solution 300 may change the
status quo to address certain critical requirements of
applications.
[0151] Conventional Linux stacks may consist of simple building
blocks, such generic memory allocation, process scheduling, file
access, memory mapping, page caching, etc. Although these are
essential for an application to run on Linux, this is not optimal
for certain categories of applications that are input/output (IO)
intensive, such as NoSQL. NoSQL applications are very IO intensive,
and it is harder to predict their data access in a generic manner.
If applications have to be deployed in a utility-computing
environment, it is not ideal for Linux to provide generic minimal
implementations of these building blocks. It is preferred for these
building blocks to be highly flexible and have application-relevant
features that can be controllable from the application(s).
[0152] Although every application has its own specific
requirements, in an exemplary embodiment, the NoSQL class of
applications has the following requirements which, when addressed
by the Linux stack, could greatly improve the performance of NoSQL
applications and other IO intensive applications. The requirements
are first, the use of file level priority. The Linux file system
should provide access level priority between different files at a
minimum. For example, an application process (consisting of
multiple threads) accessing two different files with one file given
higher priority over the other (such as one database/table/index
over the other). This would enable the precious storage I/O
resources be preferentially utilized based on the data being
accessed. One would argue that this could be indirectly addressed
by running one thread/process be run at a higher or lower priority,
but those process level priorities are not communicated over to
file system or storage components. Process or thread level
priorities are meant only for utilizing CPU resources. Moreover, it
is possible that same thread might be accessing these two files and
hence will be utilizing the storage resources at two different
levels based on what data (file) being accessed. Second, there may
be a requirement for access level preferences. A Linux file system
may provide various preferences (primarily SLA) during a session of
a file (opened file), such as priority between file sessions, the
amount of buffering of blocks, the retention/life time preferences
for various blocks, alerts for resource thresholds and contentions,
and performance statistics. As an example, when a NoSQL application
such as MongoDB or Cassandra would have two or more threads for
writes and reads, where if writes may have to be given preference
over reads, a file session for write may have to be given
preference over a file session for read for the same file. This
capability enables two sessions of the same file to have two
different priorities.
[0153] Many of the NoSQL applications store different types of data
into the same file; for example, MongoDB stores user collections as
well as (b-tree) index collections in the same set of database
files. MongoDB may want to keep the index pages (btree and
collections) in memory in preference over user collection pages.
When these files are opened, MongoDB may want to influence the
Linux, File and storage systems to treat the pages according to
MongoDB policies as opposed to treating these pages in a generic
FIFO or LRU basis agnostic of the application's requirements.
[0154] Resource alerts and performance statistics enable an NoSQL
database to understand the behavior of the underlying File and
storage system and could service its database queries accordingly
or trigger actions to be carried out such as sharding of the
database or reducing/increasing of File I/O preference for other
jobs running in the same host (such as backup, sharding, number
read/write queries serviced, etc.). For example, performance stats
about min, max and average number of IOPs and latencies as well as
top ten candidate pages thrashed in and out of host memory in a
given period of time would enable an application to fine tune
itself dynamically adjusting the parameters noted above.
[0155] A requirement may also exist for caching and tiering
preferences. A Linux file system may need to have a dynamically
configurable caching policy while applications are accessing their
files. Currently, Linux file systems typically pre-fetch contiguous
blocks of a file, hoping that applications are reading the file in
a sequential manner like a stream. Although it is true for many
legacy applications like web servers and video streamers, emerging
NoSQL applications do not follow sequential reads strictly. These
applications read blocks randomly. As an example, MongoDB stores
the document keys in index tables in b-tree, laid out flat on a
portion of a file, which, when a key is searched, accesses the
blocks randomly until it locates the key. Moreover, these files are
not dedicated to such b-tree based index tables alone. These files
are shared among various types of tables (collections) such as user
documents and system index files. Because of this, a Linux file
system cannot predict what portions of the file need to be cached,
read ahead, swapped out for efficient memory usage, etc.
[0156] In embodiments of the methods and systems described herein,
there is a common thread across various applications in their
requirements for storage. In particular, latency and IOPs for
specific types of data at specific times and places of need are
very impactful on performance of these applications.
[0157] For example, to address the host level requirements listed
above, disclosed herein are methods and systems for a well
fine-tuned file-system client that enables applications to
completely influence and control the storing, retrieving, retaining
and tiering of data according to preference within the host and
elsewhere.
[0158] As shown in FIG. 18, a File System (FS) client 1802 keeps
separate buffer pools for separate sessions of a file (fd1 and
fd2). It also pre-allocates and maintains aggregate memory pools
for each application or set of processes. The SLA-Broker 1804 may
be exercised by the application either internally within the
process/thread where the file I/O is carried out or externally from
another set of processes, to influence the FS Client 1802 to
provide appropriate storage I/O SLAs dynamically. Controlling the
SLA from an external process enables a legacy application with no
knowledge of these newer storage control features immediately
without modifying the application itself.
[0159] Methods and systems disclosed herein may provide extensive
tiering services for data retrieval across network and hosts. As
one can see in FIG. 19 below, a High Performance Distributed File
Server (DFS) 1902 enables application to run in the Platform 1904
in a containerized form to determine and execute what portions of
files should reside in which media (DRAM, NVRAM, SSD or HDDs) in
cached form storage form dynamically. These application containers
1908 can determine other storage policies such as whether a file
has to be striped, mirrored, raided and disaster recovered (DR'ed)
as well.
[0160] The methods and systems disclosed herein also provide
extensive caching service. wherein an application container in the
High Performance DFS 1902 can proactively retrieve specific pages
of a file from local storage and/or remote locations and push these
pages to specific places for fast retrieval later when needed. For
instance, the methods and systems may local memory and SSD usages
of the hosts running the application and proactively push pages of
an application's interest into any of these hosts' local
memory/SSD. The methods and systems may use the local tiers of
memory, SSD and HDD provisioned for this purpose in the DFS
platform 1904 for very low latency retrieval by the application at
a later time of its need.
[0161] The use of extending the cache across hosts of the
applications is immense. For example, in MongoDB when the working
set temporarily grows beyond its local host's memory, thrashing
happens, and it significantly reduces the query handling
performance. This is because when a needed file data page is
discarded in order to bring in a new page to satisfy a query and
subsequently, if the original page has to be brought back, the
system has to reread the page afresh from the disk subsystem,
thereby incurring huge latency in completing a query.
Application-driven storage access helps these kinds of scenarios by
keeping a cache of the discarded page elsewhere in the network (in
another application host's memory/SSD or in local tiers of storage
of the High Performance DFS system 1902) temporarily until MongoDB
requires the page again and thereby significantly reducing the
latency in completing the query.
[0162] Referring to FIG. 20, High Performance DFS 1902 takes
advantage of DRAM and SSD resources across the application hosts in
a single, unified RAM and SSD-based tier/cache 2002, in order to
cache and serve the application data as necessary and as influenced
and controlled by the application.
[0163] A system comprising of a set of hosts (H1 through HN), a
file or block server 2102 and a storage subsystem 2104 is disclosed
herein as shown in the FIG. 21. A host H1-HN is typically a
computer running an application that needs access to data
permanently or temporarily stored in storage. The file or volume
server 2102 may be a data organizer and a data server, typically
running a hardware comprising a central processing unit (CPU),
memory and special hardware to connect to external devices such as
networking and storage devices. The file or volume server 2102
organizes user data in terms of multiple fixed or variable number
of bytes called blocks. It stores these blocks of data in an
internal or external storage. A random, but logically related,
sequence of blocks is organized into a file or a volume. One or
more Hosts H1-HN can access these files or volumes through an
application programming interface (API) or any other protocol. A
file or volume server can serve one or more files and volumes to
one or more hosts. It is to be noted that a host and a file or
volume server can be in two different physical entities connected
directly or through a network or they could be logically located
together in a single physical computer.
[0164] Storage 2104 may be a collection of entities capable of
retaining a piece of data temporarily or permanently. This is
typically comprised of static or dynamic random access memory
(RAM), solid state storage (SSD), hard disk drive (HDD) or a
combination of all of these. Storage could be an independent
physical entity connected to a File or volume server 2102 through a
link or a network. It could also be integrated with file or volume
server 2102 in a single physical entity. Hence, hosts H1-HN, file
or volume server 2102 and storage 2104 could be physically
collocated in a single hardware entity.
[0165] A host is typically comprised of multiple logical entities
as shown in FIG. 22. An application 2202 typically runs in a host
and would access its data elements through an API provided by its
local operating system 2204 or any other entity in place of it. The
operating system 2204 typically has a standard API interface to
interface to a file system through their file system client 2206. A
file system client 2206 is a software entity running within the
host to interface with a file or volume server 2210 either located
remotely or locally. It would provide the data elements needed by
application 2202, which are present in a single or multiple files
or volumes, by retrieving them from file or volume server 2210 and
keeping them in the host's memory 2208 until the application
completes its processing of the elements of data. In a typical
application scenario, a specific piece of data would be read and/or
modified multiple number of times as required. It is also typical
that an entire file or volume, consisting of multiple data
elements, is potentially much larger than the size of local memory
2208 in certain types of applications. This makes operating system
2204 and file system client 2206 more complicated in its
implementation in order to decide what blocks of data to be
retained in or evicted from memory 2208 based on the prediction
that the application 2202 may or may not access them in future. So
far, the existing implementations execute some generic and
application-independent methods, such as first-in-first-out (FIFO)
or least-recently-used (LRU), to retain or evict the blocks of data
in memory in order to bring in new blocks of data from file or
volume server 2210. Moreover, when a memory occupied by a block of
data is to be reclaimed for storing another block of data, the
original data is simply erased without the consideration for its
future use. Normally, the disk subsystem in is very slow and incurs
high latency when a block of data is read from it and transferred
by file or volume server 2210 to file system client 2206 to memory
2208. So, when the original block of data is erased, the
application might have to wait longer if it tries to access the
original data in near future. The main problem with this kind of
implementation is that none of the modules in the path of data
access, namely operating system 2204, file system client 2206,
memory 2208, block server 2210 and storage have any knowledge of
what, when and how often a block of data is going be accessed by
application 2202.
[0166] An example scenario depicting an application 2202 accessing
a block of data from storage 2212 is shown in FIG. 23. The numbered
circles are to show the steps involved in the process of accessing
a block of data. These steps are explained below. First,
application 2202 uses API of file or Operating System 2204 to
access a block of data. operating system 2204 invokes an equivalent
API for file system client 2206 to access the same. Second, file
system client 2206 tries to find if the data exists in its local
memory buffers dedicated for this purpose. If found, steps (3)
through (7) below are skipped. Third, sends a command to retrieve
the data from block server 2210. Fourth, block server 2210 sends a
read command to storage 2212 to read the block of data from the
storage. Fifth, storage 2212 returns the block of data to block
server 2210 after reading it from the storage. Sixth, block server
2210 returns the block of data to file system client 2206. Seventh,
file system client 2206 saves the data in a memory buffer in memory
2208 for any future access. Eighth, file system client 2206 returns
the requested data to the application 2202.
[0167] In the methods and systems disclosed herein, in order to
address performance requirements related to data access by most
newer class of applications in the area of NoSQL and BigData, it is
proposed that the components in the data block access comprising
operating system 2204, file system client 2206, memory 2208, block
server 2210 and storage 2212 be controlled by any application 2202.
Namely, we propose the following. First, enable operating system
2204 to provide additional API to allow applications to control
file system client 2206. Second, enhance file system client 2206 to
support the following: (a) allow application 2202 to create a
dedicated pool of memory in memory 2208 for a particular file or
volume, in the sense, a file or volume will have a dedicated pool
of memory buffers to hold data specific to it which are not shared
or removed for the purposes of other files or volumes; (b) allow
application 2202 to create a dedicated pool of memory in memory
2208 for a particular session with a file or volume such that two
independent sessions with a file or volume will have independent
memory buffers to hold their data. As an example, a critically
important file session may have large number of memory buffers in
memory 2208, so that the session can take advantage of more data
being present for quicker and frequent access, whereas a second
session with the same file may be assigned with very few buffers
and hence it might have to incur more delay and reuse of its
buffers to access various parts of the file; (c) allow application
2202 to create an extended pool of buffers beyond memory 2208
across other hosts or block server 2210 for quicker access. This
enables blocks of data be kept in memory 2208 of other hosts as
well as any memory 2402 present in the file or block server 2210;
(d) allow application 2202 to make any block of data to be more
persistent in memory 2208 relative to other blocks of data for a
file, volume or a session. This allows an application to pick and
choose a block of data to be always available for immediate access
and not let operating system 2204 or file system client 2206 to
evict it based on their own eviction policies; and (e) allow
application 2202 to make any block of data to be less persistent in
memory 2208 relative to other blocks of data for a file, volume or
a session. This allows an application to let know operating system
2204 and file system client 2206 to evict and reuse the buffer of
the data block as and when they choose to. This helps in retaining
other normal blocks of data for longer period of time. Third,
enable block server 2210 to host application specific modules in
terms of application container 2400 as shown in the FIG. 24 with
the following capabilities: (a) enable application container 2400
to fetch blocks of data of interest to application 2202 ahead of
time and store them in local memory 2402 for later quick access and
avoid the latency penalty associated with storage 2212 and (b)
enable storing of evicted pages from memory 2208 of hosts in local
memory 2402 for any later access by application 2202.
[0168] The application driven feature of (2)(c) above needs further
explanation. There are two scenarios. The first one involves block
of data being retrieved from the memory of block server 2210. The
other scenario involves retrieving the same from another host.
Assuming the exact same block data has been read from storage 2212
by two hosts (H1) and (H2), the methods and systems disclosed
herein provide a system such as depicted in FIG. 25. When a block
of data is noticed to be present in another host (H2), it is
directly retrieved from it by file system client 2206 instead
asking block server 2210 to retrieve it from storage 2212, which
will be slower and incurs high latency.
[0169] In embodiments, if file system client 2206 decides to evict
a block of data from (D1) because of storing a more important block
of data in its place, file system client 2206 could send the
evicted block of data to file system client 2206' to be stored in
memory 2208' on its behalf.
[0170] It should be noted that the abovementioned techniques can be
applied to achieving fast failover in case of failure(s) of Hosts.
Furthermore the caching techniques described above; especially
pertaining to RAM can use used to achieve failover with a warm
cache. FIG. 25 shows an example of a fast failover system with a
warm cache. The end result is that during a failure of a node, the
end application on a new node will not undergo a time period before
the cache (in RAM) is warmed and thereby incur a period of lower
application performance.
[0171] Provided herein is a system and method with a processor and
a file server with an application specific module to control the
storage access according to the application's needs.
[0172] Also provided herein is a system and method with a processor
and a data (constituting blocks of fixed size bytes, similar or
different objects with variable number of bytes) storage enabling
an application specific module to control the storage access
according to the application's needs.
[0173] Also provided herein is a system and method which retrieves
a stale file or storage data block, previously maintained for the
purposes of an application's use, from a host's memory and/or its
temporary or permanent storage element and stores it in another
host's memory or and/or its temporary or permanent storage element,
for the purposes of use by the application at a later time.
[0174] Also provided herein is a system and method which retrieves
any file or storage data block, previously maintained for the
purposes of an application's use, from a host's memory and/or its
temporary or permanent storage element and stores it in another
host's memory or and/or its temporary or permanent storage element,
for the purposes of use by the application at a later time.
[0175] Also provided herein is a system and method which utilizes
memory and/or its temporary or permanent storage element of a host
to store any file or storage data block which would be subsequently
accessed by an application running in another host for the purposes
of reducing latency of data access.
[0176] File or storage data blocks, previously maintained for the
purposes of an application's use, from a host's memory and/or its
temporary or permanent storage element, may be stored in another
host's memory or and/or its temporary or permanent storage element,
for the purposes of use by the application at a later time.
[0177] The mechanism of transferring a file or storage data block,
previously maintained for the purposes of an application's use,
from a host's memory and/or its temporary or permanent storage
element to another host over a network.
[0178] In accordance with various exemplary and non-limiting
embodiments, there is disclosed a device comprising a converged
input/output controller that includes a physical target storage
media controller, a physical network interface controller and a
gateway between the storage media controller and the network
interface controller, wherein gateway provides a direct connection
for storage traffic and network traffic between the storage media
controller and the network interface controller.
[0179] In accordance with some embodiments, the device may further
comprise a virtual storage interface that presents storage media
controlled by the storage media controller as locally attached
storage, regardless of the location of the storage media. In
accordance with yet other embodiments, the device may further
comprise a virtual storage interface that presents storage media
controlled by the storage media controller as locally attached
storage, regardless of the type of the storage media. In accordance
with yet other embodiments, the device may further comprise a
virtual storage interface that facilitates dynamic provisioning of
the storage media, wherein the physical storage may be either local
or remote.
[0180] In accordance with yet other embodiments, the device may
further comprise a virtual network interface that facilitates
dynamic provisioning of the storage media, wherein the physical
storage may be either local or remote. In accordance with yet other
embodiments, the device may be adapted to be installed as a
controller card on a host computing system, in particular, wherein
the gateway operates without intervention by the operating system
of the host computing system.
[0181] In accordance with yet other embodiments, the device may
include at least one field programmable gate array providing at
least one of the storage functions and the network functions of the
device. In accordance with yet other embodiments, the device may be
configured as a network-deployed switch. In accordance with yet
other embodiments, the device may further comprise a functional
component of the device for translating storage media instructions
between a first protocol and at least one other protocol.
[0182] With reference to FIG. 26, there is illustrated an exemplary
and non-limiting method of virtualization of a storage device.
First, at step 2600 there is accessed a physical storage device
that responds to instructions in a first storage protocol. Next, at
step 2602, there are translated instructions between the first
storage protocol and a second storage protocol. Lastly, at step
2604, using the second protocol, the physical storage device is
presented to an operating system, such that the storage of the
physical storage device can be dynamically provisioned, whether the
physical storage device is local or remote to a host computing
system that uses the operating system.
[0183] In accordance with various embodiments, the first protocol
is at least one of a SATA protocol, an NVMe protocol, a SAS
protocol, an iSCSI protocol, a fiber channel protocol and a fiber
channel over Ethernet protocol. In other embodiments, the second
protocol is an NVMe protocol.
[0184] In some embodiments, the method may further comprise
providing an interface between an operating system and a device
that performs the translation of instructions between the first and
second storage protocols and/or providing an NVMe over Ethernet
connection between the device that performs the translation of
instructions and a remote, network-deployed storage device.
[0185] With reference to FIG. 27, there is illustrated an exemplary
and non-limiting method of facilitating migration of at least one
of an application and a container. First, at step 2700, there is
provided a converged storage and networking controller, wherein a
gateway provides a connection for network and storage traffic
between a storage component and a networking component of the
device without intervention of the operating system of a host
computer. Next, at step 2702, the at least one application or
container is mapped to a target physical storage device that is
controlled by the converged storage and networking controller, such
that the application or container can access the target physical
storage, without intervention of the operating system of the host
system to which the target physical storage is attached, when the
application or container is moved to another computing system.
[0186] In accordance with various embodiments, the migration is of
a Linux container or a scaleout application.
[0187] In accordance with yet other embodiments, the target
physical storage is a network-deployed storage device that uses at
least one of an iSCSI protocol, a fiber channel protocol and a
fiber channel over Ethernet protocol. In yet other embodiments, the
target physical storage is a disk attached storage device that uses
at least one of a SAS protocol, a SATA protocol and an NVMe
protocol.
[0188] With reference to FIG. 28, there is illustrated an exemplary
and non-limiting method of providing quality of service (QoS) for a
network. First, at step 2800, there is provided a converged storage
and networking controller, wherein a gateway provides a connection
for network and storage traffic between a storage component and a
networking component of the device without intervention of the
operating system of a host computer. Next, at step 2802, without
intervention of the operating system of a host computer, there is
managed at least one quality of service (QoS) parameter related to
a network in the data path of which the storage and networking
controller is deployed, such managing being based on at least one
of the storage traffic and the network traffic that is handled by
the converged storage and networking controller.
[0189] While only a few embodiments of the present disclosure have
been shown and described, it will be obvious to those skilled in
the art that many changes and modifications may be made thereunto
without departing from the spirit and scope of the present
disclosure as described in the following claims. All patent
applications and patents, both foreign and domestic, and all other
publications referenced herein are incorporated herein in their
entireties to the full extent permitted by law.
[0190] The methods and systems described herein may be deployed in
part or in whole through a machine that executes computer software,
program codes, and/or instructions on a processor. The present
disclosure may be implemented as a method on the machine, as a
system or apparatus as part of or in relation to the machine, or as
a computer program product embodied in a computer readable medium
executing on one or more of the machines. In embodiments, the
processor may be part of a server, cloud server, client, network
infrastructure, mobile computing platform, stationary computing
platform, or other computing platform. A processor may be any kind
of computational or processing device capable of executing program
instructions, codes, binary instructions and the like. The
processor may be or may include a signal processor, digital
processor, embedded processor, microprocessor or any variant such
as a co-processor (math co-processor, graphic co-processor,
communication co-processor and the like) and the like that may
directly or indirectly facilitate execution of program code or
program instructions stored thereon. In addition, the processor may
enable execution of multiple programs, threads, and codes. The
threads may be executed simultaneously to enhance the performance
of the processor and to facilitate simultaneous operations of the
application. By way of implementation, methods, program codes,
program instructions and the like described herein may be
implemented in one or more thread. The thread may spawn other
threads that may have assigned priorities associated with them; the
processor may execute these threads based on priority or any other
order based on instructions provided in the program code. The
processor, or any machine utilizing one, may include non-transitory
memory that stores methods, codes, instructions and programs as
described herein and elsewhere. The processor may access a
non-transitory storage medium through an interface that may store
methods, codes, and instructions as described herein and elsewhere.
The storage medium associated with the processor for storing
methods, programs, codes, program instructions or other type of
instructions capable of being executed by the computing or
processing device may include but may not be limited to one or more
of a CD-ROM, DVD, memory, hard disk, flash drive, RAM, ROM, cache
and the like.
[0191] A processor may include one or more cores that may enhance
speed and performance of a multiprocessor. In embodiments, the
process may be a dual core processor, quad core processors, other
chip-level multiprocessor and the like that combine two or more
independent cores (called a die).
[0192] The methods and systems described herein may be deployed in
part or in whole through a machine that executes computer software
on a server, client, firewall, gateway, hub, router, or other such
computer and/or networking hardware. The software program may be
associated with a server that may include a file server, print
server, domain server, internet server, intranet server, cloud
server, and other variants such as secondary server, host server,
distributed server and the like. The server may include one or more
of memories, processors, computer readable media, storage media,
ports (physical and virtual), communication devices, and interfaces
capable of accessing other servers, clients, machines, and devices
through a wired or a wireless medium, and the like. The methods,
programs, or codes as described herein and elsewhere may be
executed by the server. In addition, other devices required for
execution of methods as described in this application may be
considered as a part of the infrastructure associated with the
server.
[0193] The server may provide an interface to other devices
including, without limitation, clients, other servers, printers,
database servers, print servers, file servers, communication
servers, distributed servers, social networks, and the like.
Additionally, this coupling and/or connection may facilitate remote
execution of program across the network. The networking of some or
all of these devices may facilitate parallel processing of a
program or method at one or more location without deviating from
the scope of the disclosure. In addition, any of the devices
attached to the server through an interface may include at least
one storage medium capable of storing methods, programs, code
and/or instructions. A central repository may provide program
instructions to be executed on different devices. In this
implementation, the remote repository may act as a storage medium
for program code, instructions, and programs.
[0194] The software program may be associated with a client that
may include a file client, print client, domain client, internet
client, intranet client and other variants such as secondary
client, host client, distributed client and the like. The client
may include one or more of memories, processors, computer readable
media, storage media, ports (physical and virtual), communication
devices, and interfaces capable of accessing other clients,
servers, machines, and devices through a wired or a wireless
medium, and the like. The methods, programs, or codes as described
herein and elsewhere may be executed by the client. In addition,
other devices required for execution of methods as described in
this application may be considered as a part of the infrastructure
associated with the client.
[0195] The client may provide an interface to other devices
including, without limitation, servers, other clients, printers,
database servers, print servers, file servers, communication
servers, distributed servers and the like. Additionally, this
coupling and/or connection may facilitate remote execution of
program across the network. The networking of some or all of these
devices may facilitate parallel processing of a program or method
at one or more location without deviating from the scope of the
disclosure. In addition, any of the devices attached to the client
through an interface may include at least one storage medium
capable of storing methods, programs, applications, code and/or
instructions. A central repository may provide program instructions
to be executed on different devices. In this implementation, the
remote repository may act as a storage medium for program code,
instructions, and programs.
[0196] The methods and systems described herein may be deployed in
part or in whole through network infrastructures. The network
infrastructure may include elements such as computing devices,
servers, routers, hubs, firewalls, clients, personal computers,
communication devices, routing devices and other active and passive
devices, modules and/or components as known in the art. The
computing and/or non-computing device(s) associated with the
network infrastructure may include, apart from other components, a
storage medium such as flash memory, buffer, stack, RAM, ROM and
the like. The processes, methods, program codes, instructions
described herein and elsewhere may be executed by one or more of
the network infrastructural elements. The methods and systems
described herein may be adapted for use with any kind of private,
community, or hybrid cloud computing network or cloud computing
environment, including those which involve features of software as
a service (SaaS), platform as a service (PaaS), and/or
infrastructure as a service (IaaS).
[0197] The methods, program codes, and instructions described
herein and elsewhere may be implemented on a cellular network has
sender-controlled contact media content item multiple cells. The
cellular network may either be frequency division multiple access
(FDMA) network or code division multiple access (CDMA) network. The
cellular network may include mobile devices, cell sites, base
stations, repeaters, antennas, towers, and the like. The cell
network may be a GSM, GPRS, 3G, EVDO, mesh, or other networks
types.
[0198] The methods, program codes, and instructions described
herein and elsewhere may be implemented on or through mobile
devices. The mobile devices may include navigation devices, cell
phones, mobile phones, mobile personal digital assistants, laptops,
palmtops, netbooks, pagers, electronic books readers, music players
and the like. These devices may include, apart from other
components, a storage medium such as a flash memory, buffer, RAM,
ROM and one or more computing devices. The computing devices
associated with mobile devices may be enabled to execute program
codes, methods, and instructions stored thereon. Alternatively, the
mobile devices may be configured to execute instructions in
collaboration with other devices. The mobile devices may
communicate with base stations interfaced with servers and
configured to execute program codes. The mobile devices may
communicate on a peer-to-peer network, mesh network, or other
communications network. The program code may be stored on the
storage medium associated with the server and executed by a
computing device embedded within the server. The base station may
include a computing device and a storage medium. The storage device
may store program codes and instructions executed by the computing
devices associated with the base station.
[0199] The computer software, program codes, and/or instructions
may be stored and/or accessed on machine readable media that may
include: computer components, devices, and recording media that
retain digital data used for computing for some interval of time;
semiconductor storage known as random access memory (RAM); mass
storage typically for more permanent storage, such as optical
discs, forms of magnetic storage like hard disks, tapes, drums,
cards and other types; processor registers, cache memory, volatile
memory, non-volatile memory; optical storage such as CD, DVD;
removable media such as flash memory (e.g. USB sticks or keys),
floppy disks, magnetic tape, paper tape, punch cards, standalone
RAM disks, Zip drives, removable mass storage, off-line, and the
like; other computer memory such as dynamic memory, static memory,
read/write storage, mutable storage, read only, random access,
sequential access, location addressable, file addressable, content
addressable, network attached storage, storage area network, bar
codes, magnetic ink, and the like.
[0200] The methods and systems described herein may transform
physical and/or or intangible items from one state to another. The
methods and systems described herein may also transform data
representing physical and/or intangible items from one state to
another.
[0201] The elements described and depicted herein, including in
flow charts and block diagrams throughout the figures, imply
logical boundaries between the elements. However, according to
software or hardware engineering practices, the depicted elements
and the functions thereof may be implemented on machines through
computer executable media has sender-controlled contact media
content item a processor capable of executing program instructions
stored thereon as a monolithic software structure, as standalone
software modules, or as modules that employ external routines,
code, services, and so forth, or any combination of these, and all
such implementations may be within the scope of the present
disclosure. Examples of such machines may include, but may not be
limited to, personal digital assistants, laptops, personal
computers, mobile phones, other handheld computing devices, medical
equipment, wired or wireless communication devices, transducers,
chips, calculators, satellites, tablet PCs, electronic books,
gadgets, electronic devices, devices has sender-controlled contact
media content item artificial intelligence, computing devices,
networking equipment, servers, routers and the like. Furthermore,
the elements depicted in the flow chart and block diagrams or any
other logical component may be implemented on a machine capable of
executing program instructions. Thus, while the foregoing drawings
and descriptions set forth functional aspects of the disclosed
systems, no particular arrangement of software for implementing
these functional aspects should be inferred from these descriptions
unless explicitly stated or otherwise clear from the context.
Similarly, it will be appreciated that the various steps identified
and described above may be varied, and that the order of steps may
be adapted to particular applications of the techniques disclosed
herein. All such variations and modifications are intended to fall
within the scope of this disclosure. As such, the depiction and/or
description of an order for various steps should not be understood
to require a particular order of execution for those steps, unless
required by a particular application, or explicitly stated or
otherwise clear from the context.
[0202] The methods and/or processes described above, and steps
associated therewith, may be realized in hardware, software or any
combination of hardware and software suitable for a particular
application. The hardware may include a general-purpose computer
and/or dedicated computing device or specific computing device or
particular aspect or component of a specific computing device. The
processes may be realized in one or more microprocessors,
microcontrollers, embedded microcontrollers, programmable digital
signal processors or other programmable device, along with internal
and/or external memory. The processes may also, or instead, be
embodied in an application specific integrated circuit, a
programmable gate array, programmable array logic, or any other
device or combination of devices that may be configured to process
electronic signals. It will further be appreciated that one or more
of the processes may be realized as a computer executable code
capable of being executed on a machine-readable medium.
[0203] The computer executable code may be created using a
structured programming language such as C, an object oriented
programming language such as C++, or any other high-level or
low-level programming language (including assembly languages,
hardware description languages, and database programming languages
and technologies) that may be stored, compiled or interpreted to
run on one of the above devices, as well as heterogeneous
combinations of processors, processor architectures, or
combinations of different hardware and software, or any other
machine capable of executing program instructions.
[0204] Thus, in one aspect, methods described above and
combinations thereof may be embodied in computer executable code
that, when executing on one or more computing devices, performs the
steps thereof. In another aspect, the methods may be embodied in
systems that perform the steps thereof, and may be distributed
across devices in a number of ways, or all of the functionality may
be integrated into a dedicated, standalone device or other
hardware. In another aspect, the means for performing the steps
associated with the processes described above may include any of
the hardware and/or software described above. All such permutations
and combinations are intended to fall within the scope of the
present disclosure.
[0205] While the disclosure has been disclosed in connection with
the preferred embodiments shown and described in detail, various
modifications and improvements thereon will become readily apparent
to those skilled in the art. Accordingly, the spirit and scope of
the present disclosure is not to be limited by the foregoing
examples, but is to be understood in the broadest sense allowable
by law.
[0206] The use of the terms "a" and "an" and "the" and similar
referents in the context of describing the disclosure (especially
in the context of the following claims) is to be construed to cover
both the singular and the plural, unless otherwise indicated herein
or clearly contradicted by context. The terms "comprising," "haa
sender-controlled contact media content item," "including," and
"containing" are to be construed as open-ended terms (i.e., meaning
"including, but not limited to,") unless otherwise noted.
Recitation of ranges of values herein are merely intended to serve
as a shorthand method of referring individually to each separate
value falling within the range, unless otherwise indicated herein,
and each separate value is incorporated into the specification as
if it were individually recited herein. All methods described
herein can be performed in any suitable order unless otherwise
indicated herein or otherwise clearly contradicted by context. The
use of any and all examples, or exemplary language (e.g., "such
as") provided herein, is intended merely to better illuminate the
disclosure and does not pose a limitation on the scope of the
disclosure unless otherwise claimed. No language in the
specification should be construed as indicating any non-claimed
element as essential to the practice of the disclosure.
[0207] While the foregoing written description enables one of
ordinary skill to make and use what is considered presently to be
the best mode thereof, those of ordinary skill will understand and
appreciate the existence of variations, combinations, and
equivalents of the specific embodiment, method, and examples
herein. The disclosure should therefore not be limited by the above
described embodiment, method, and examples, but by all embodiments
and methods within the scope and spirit of the disclosure.
[0208] All documents referenced herein are hereby incorporated by
reference.
* * * * *