U.S. patent application number 15/057213 was filed with the patent office on 2017-04-06 for dynamic aggressiveness for optimizing placement of virtual machines in a computing environment.
The applicant listed for this patent is International Business Machines Corporation. Invention is credited to Joseph W. Cropper, Jennifer D. Mulsow, Taylor D. Peoples, Edward Shvartsman.
Application Number | 20170097834 15/057213 |
Document ID | / |
Family ID | 58227706 |
Filed Date | 2017-04-06 |
United States Patent
Application |
20170097834 |
Kind Code |
A1 |
Cropper; Joseph W. ; et
al. |
April 6, 2017 |
DYNAMIC AGGRESSIVENESS FOR OPTIMIZING PLACEMENT OF VIRTUAL MACHINES
IN A COMPUTING ENVIRONMENT
Abstract
Dynamically changing the aggressiveness of optimization of
virtual machines on physical hosts allows more efficient and varied
optimization. An aggressiveness policy mechanism periodically
applies system conditions to the aggressiveness policies to create
aggressiveness settings that are provided to an optimizer. The
optimizer then uses the aggressiveness settings to dynamically
adjust the aggressiveness of placement of virtual machines
according to the aggressiveness settings and consistent with other
optimization policies. The aggressiveness policy mechanism may
allow a system administrator to create and/or select aggressiveness
policies.
Inventors: |
Cropper; Joseph W.;
(Rochester, MN) ; Mulsow; Jennifer D.; (Cedar
Park, TX) ; Peoples; Taylor D.; (Austin, TX) ;
Shvartsman; Edward; (Austin, TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation |
Armonk |
NY |
US |
|
|
Family ID: |
58227706 |
Appl. No.: |
15/057213 |
Filed: |
March 1, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14872284 |
Oct 1, 2015 |
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15057213 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 9/5077 20130101;
G06F 2009/45575 20130101; H04L 41/0816 20130101; G06F 2009/45595
20130101; H04L 67/1008 20130101; G06F 9/45504 20130101; G06F
9/45558 20130101; G06F 9/44505 20130101; H04L 41/083 20130101; G06F
2009/4557 20130101; H04L 41/0893 20130101; H04L 41/0806 20130101;
G06F 9/4856 20130101 |
International
Class: |
G06F 9/445 20060101
G06F009/445; G06F 9/48 20060101 G06F009/48; G06F 9/455 20060101
G06F009/455 |
Claims
1.-19. (canceled)
20. An apparatus comprising: at least one processor; a memory
coupled to the at least one processor; a first physical host with a
virtual machine and a second physical host coupled to the apparatus
via a network; an optimizer for optimizing the loading of virtual
machines on host computers; an aggressiveness policy mechanism
residing in the memory and executed by the at least one processor
that provides dynamically changing the aggressiveness settings for
loading the virtual machines based on aggressiveness policies that
indicate to change aggressiveness settings depending on a system
condition; wherein the optimizer dynamically changes the
aggressiveness of optimization as indicated by the dynamically
changing aggressiveness settings; wherein the aggressiveness policy
mechanism allows a system administrator to define one or more
aggressiveness policies that are used to determine the
aggressiveness settings; wherein the at least one system condition
is chosen from the following: number of migration failures in the
past, the number of network connections for a physical host, the
number of packets dropped on a network connection, number of
deployments in the past, the total number of virtual machines in
the system, the total number of hosts in the system; wherein the
aggressiveness settings comprise: a maximum number of migrations
per host per hour, a maximum number of migrations per cloud per
hour, a maximum number of concurrent migrations per host and a
maximum number of concurrent migrations per cloud; and wherein the
aggressiveness policy mechanism periodically evaluates the
aggressiveness policies to dynamically update the aggressiveness
settings used by the optimizer to determine whether to migrate the
virtual machine to another physical host.
Description
BACKGROUND
[0001] 1. Technical Field
[0002] This invention generally relates to virtual machines in a
computing environment, and more specifically relates to dynamically
optimizing placement of virtual machines on physical hosts in a
computing environment using one or more policies that define
aggressiveness settings for the optimizer.
[0003] 2. Background Art
[0004] Cloud computing is a common expression for distributed
computing over a network and can also be used with reference to
network-based services such as Infrastructure as a Service (IaaS).
IaaS is a cloud based service that provides physical processing
resources to run virtual machines (VMs) as a guest for different
customers. The virtual machine may host a user application or a
server.
[0005] A computing environment, such as a cloud computing
environment, may have a large number of physical machines that can
each host one or more virtual machines. Prior art cloud management
tools allow a system administrator to assist in determining a
specific physical host in which to place or deploy a new virtual
machine. After deployment, the cloud management tools optimize the
system by moving one or more virtual machines to a different
physical host. The placement of the new virtual machine initially
and during optimization may be determined by a placement policy
selected by the system administrator. Prior art placement policies
include fixed aggressiveness policies that define limited settings
for aggressiveness of optimization.
BRIEF SUMMARY
[0006] An apparatus and method for dynamically changing
aggressiveness used to optimize placement of virtual machines on
physical hosts to allow more efficient and varied optimization. An
aggressiveness policy mechanism periodically applies system
conditions to the aggressiveness policies to create aggressiveness
settings that are provided to an optimizer. The optimizer then uses
the aggressiveness settings to dynamically adjust the
aggressiveness of placement of virtual machines according to the
aggressiveness settings and consistent with other optimization
policies. The aggressiveness policy mechanism may allow a system
administrator to create and/or select aggressiveness policies.
[0007] The foregoing and other features and advantages of the
invention will be apparent from the following more particular
description of preferred embodiments of the invention, as
illustrated in the accompanying drawings.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
[0008] The disclosure will be described in conjunction with the
appended drawings, where like designations denote like elements,
and:
[0009] FIG. 1 is a block diagram of a cloud computing node;
[0010] FIG. 2 is a block diagram of a cloud computing
environment;
[0011] FIG. 3 is a block diagram of abstraction model layers;
[0012] FIG. 4 is a block diagram that illustrates a computer system
with an aggressiveness policy mechanism as described herein that
provides dynamic aggressiveness in optimizing placement of virtual
machines on physical hosts;
[0013] FIG. 5 is a block diagram that illustrates a simplified
example of dynamically changing the aggressiveness of optimization
of the placement of virtual machines on host computers;
[0014] FIG. 6 is a flow diagram of a method for dynamically
changing aggressiveness in optimizing placement of virtual machines
on physical hosts as described herein; and
[0015] FIG. 7 is a flow diagram of an example method for step 630
in FIG. 6.
DETAILED DESCRIPTION
[0016] The claims and disclosure herein describe dynamically
changing aggressiveness used to optimize placement of virtual
machines on physical hosts to allow more efficient and varied
optimization. An aggressiveness policy mechanism periodically
applies system conditions to the aggressiveness policies to create
aggressiveness settings that are provided to an optimizer. The
optimizer then uses the aggressiveness settings to dynamically
adjust the aggressiveness of placement of virtual machines
according to the aggressiveness settings and consistent with other
optimization policies. The aggressiveness policy mechanism may
allow a system administrator to create and/or select aggressiveness
policies.
[0017] It is understood in advance that although this disclosure
includes a detailed description on cloud computing, implementation
of the teachings recited herein are not limited to a cloud
computing environment. Rather, embodiments of the present invention
are capable of being implemented in conjunction with any other type
of computing environment now known or later developed.
[0018] Cloud computing is a model of service delivery for enabling
convenient, on-demand network access to a shared pool of
configurable computing resources (e.g. networks, network bandwidth,
servers, processing, memory, storage, applications, virtual
machines, and services) that can be rapidly provisioned and
released with minimal management effort or interaction with a
provider of the service. This cloud model may include at least five
characteristics, at least three service models, and at least four
deployment models.
[0019] Characteristics are as follows:
[0020] On-demand self-service: a cloud consumer can unilaterally
provision computing capabilities, such as server time and network
storage, as needed automatically without requiring human
interaction with the service's provider.
[0021] Broad network access: capabilities are available over a
network and accessed through standard mechanisms that promote use
by heterogeneous thin or thick client platforms (e.g., mobile
phones, laptops, and PDAs).
[0022] Resource pooling: the provider's computing resources are
pooled to serve multiple consumers using a multi-tenant model, with
different physical and virtual resources dynamically assigned and
reassigned according to demand. There is a sense of location
independence in that the consumer generally has no control or
knowledge over the exact location of the provided resources but may
be able to specify location at a higher level of abstraction (e.g.,
country, state, or datacenter).
[0023] Rapid elasticity: capabilities can be rapidly and
elastically provisioned, in some cases automatically, to quickly
scale out and rapidly released to quickly scale in. To the
consumer, the capabilities available for provisioning often appear
to be unlimited and can be purchased in any quantity at any
time.
[0024] Measured service: cloud systems automatically control and
optimize resource use by leveraging a metering capability at some
level of abstraction appropriate to the type of service (e.g.,
storage, processing, bandwidth, and active user accounts). Resource
usage can be monitored, controlled, and reported providing
transparency for both the provider and consumer of the utilized
service.
[0025] Service Models are as follows:
[0026] Software as a Service (SaaS): the capability provided to the
consumer is to use the provider's applications running on a cloud
infrastructure. The applications are accessible from various client
devices through a thin client interface such as a web browser
(e.g., web-based email). The consumer does not manage or control
the underlying cloud infrastructure including network, servers,
operating systems, storage, or even individual application
capabilities, with the possible exception of limited user-specific
application configuration settings.
[0027] Platform as a Service (PaaS): the capability provided to the
consumer is to deploy onto the cloud infrastructure
consumer-created or acquired applications created using programming
languages and tools supported by the provider. The consumer does
not manage or control the underlying cloud infrastructure including
networks, servers, operating systems, or storage, but has control
over the deployed applications and possibly application hosting
environment configurations.
[0028] Infrastructure as a Service (IaaS): the capability provided
to the consumer is to provision processing, storage, networks, and
other fundamental computing resources where the consumer is able to
deploy and run arbitrary software, which can include operating
systems and applications. The consumer does not manage or control
the underlying cloud infrastructure but has control over operating
systems, storage, deployed applications, and possibly limited
control of select networking components (e.g., host firewalls).
[0029] Deployment Models are as follows:
[0030] Private cloud: the cloud infrastructure is operated solely
for an organization. It may be managed by the organization or a
third party and may exist on-premises or off-premises.
[0031] Community cloud: the cloud infrastructure is shared by
several organizations and supports a specific community that has
shared concerns (e.g., mission, security requirements, policy, and
compliance considerations). It may be managed by the organizations
or a third party and may exist on-premises or off-premises.
[0032] Public cloud: the cloud infrastructure is made available to
the general public or a large industry group and is owned by an
organization selling cloud services.
[0033] Hybrid cloud: the cloud infrastructure is a composition of
two or more clouds (private, community, or public) that remain
unique entities but are bound together by standardized or
proprietary technology that enables data and application
portability (e.g., cloud bursting for loadbalancing between
clouds).
[0034] A cloud computing environment is service oriented with a
focus on statelessness, low coupling, modularity, and semantic
interoperability. At the heart of cloud computing is an
infrastructure comprising a network of interconnected nodes.
[0035] Referring now to FIG. 1, a block diagram of an example of a
cloud computing node is shown. Cloud computing node 100 is only one
example of a suitable cloud computing node and is not intended to
suggest any limitation as to the scope of use or functionality of
embodiments of the invention described herein. Regardless, cloud
computing node 100 is capable of being implemented and/or
performing any of the functionality set forth hereinabove.
[0036] In cloud computing node 100 there is a computer
system/server 110, which is operational with numerous other general
purpose or special purpose computing system environments or
configurations. Examples of well-known computing systems,
environments, and/or configurations that may be suitable for use
with computer system/server 110 include, but are not limited to,
personal computer systems, server computer systems, thin clients,
thick clients, handheld or laptop devices, multiprocessor systems,
microprocessor-based systems, set top boxes, programmable consumer
electronics, network PCs, minicomputer systems, mainframe computer
systems, and distributed cloud computing environments that include
any of the above systems or devices, and the like.
[0037] Computer system/server 110 may be described in the general
context of computer system executable instructions, such as program
modules, being executed by a computer system. Generally, program
modules may include routines, programs, objects, components, logic,
data structures, and so on that perform particular tasks or
implement particular abstract data types. Computer system/server
110 may be practiced in distributed cloud computing environments
where tasks are performed by remote processing devices that are
linked through a communications network. In a distributed cloud
computing environment, program modules may be located in both local
and remote computer system storage media including memory storage
devices.
[0038] As shown in FIG. 1, computer system/server 110 in cloud
computing node 100 is shown in the form of a general-purpose
computing device. The components of computer system/server 110 may
include, but are not limited to, one or more processors or
processing units 120, a system memory 130, and a bus 122 that
couples various system components including system memory 130 to
processor 120.
[0039] Bus 122 represents one or more of any of several types of
bus structures, including a memory bus or memory controller, a
peripheral bus, an accelerated graphics port, and a processor or
local bus using any of a variety of bus architectures. By way of
example, and not limitation, such architectures include Industry
Standard Architecture (ISA) bus, Micro Channel Architecture (MCA)
bus, Enhanced ISA (EISA) bus, Video Electronics Standards
Association (VESA) local bus, and Peripheral Component Interconnect
(PCI) bus.
[0040] Computer system/server 110 typically includes a variety of
computer system readable media. Such media may be any available
media that is accessible by computer system/server 110, and it
includes both volatile and non-volatile media, removable and
non-removable media.
[0041] System memory 130 can include computer system readable media
in the form of volatile, such as random access memory (RAM) 134,
and/or cache memory 136. Computer system/server 110 may further
include other removable/non-removable, volatile/non-volatile
computer system storage media. By way of example only, storage
system 140 can be provided for reading from and writing to a
non-removable, non-volatile magnetic media (not shown and typically
called a "hard drive"). Although not shown, a magnetic disk drive
for reading from and writing to a removable, non-volatile magnetic
disk (e.g., a "floppy disk"), and an optical disk drive for reading
from or writing to a removable, non-volatile optical disk such as a
CD-ROM, DVD-ROM or other optical media can be provided. In such
instances, each can be connected to bus 122 by one or more data
media interfaces. As will be further depicted and described below,
memory 130 may include at least one program product having a set
(e.g., at least one) of program modules that are configured to
carry out the functions described in more detail below.
[0042] Program/utility 150, having a set (at least one) of program
modules 152, may be stored in memory 130 by way of example, and not
limitation, as well as an operating system, one or more application
programs, other program modules, and program data. Each of the
operating system, one or more application programs, other program
modules, and program data or some combination thereof, may include
an implementation of a networking environment. Program modules 152
generally carry out the functions and/or methodologies of
embodiments of the invention as described herein.
[0043] Computer system/server 110 may also communicate with one or
more external devices 190 such as a keyboard, a pointing device, a
display 180, a disk drive, etc.; one or more devices that enable a
user to interact with computer system/server 110; and/or any
devices (e.g., network card, modem, etc.) that enable computer
system/server 110 to communicate with one or more other computing
devices. Such communication can occur via Input/Output (I/O)
interfaces 170. Still yet, computer system/server 110 can
communicate with one or more networks such as a local area network
(LAN), a general wide area network (WAN), and/or a public network
(e.g., the Internet) via network adapter 160. As depicted, network
adapter 160 communicates with the other components of computer
system/server 110 via bus 122. It should be understood that
although not shown, other hardware and/or software components could
be used in conjunction with computer system/server 110. Examples,
include, but are not limited to: microcode, device drivers,
redundant processing units, external disk drive arrays, RAID
systems, tape drives, data archival storage systems, etc.
[0044] Referring now to FIG. 2, illustrative cloud computing
environment 200 is depicted. As shown, cloud computing environment
200 comprises one or more cloud computing nodes 100 with which
local computing devices used by cloud consumers, such as, for
example, personal digital assistant (PDA) or cellular telephone
210A, desktop computer 210B, laptop computer 210C, and/or
automobile computer system 210N may communicate. Nodes 100 may
communicate with one another. They may be grouped (not shown)
physically or virtually, in one or more networks, such as Private,
Community, Public, or Hybrid clouds as described hereinabove, or a
combination thereof. This allows cloud computing environment 200 to
offer infrastructure, platforms and/or software as services for
which a cloud consumer does not need to maintain resources on a
local computing device. It is understood that the types of
computing devices 210A-N shown in FIG. 2 are intended to be
illustrative only and that computing nodes 100 and cloud computing
environment 200 can communicate with any type of computerized
device over any type of network and/or network addressable
connection (e.g., using a web browser).
[0045] Referring now to FIG. 3, a set of functional abstraction
layers provided by cloud computing environment 200 (FIG. 2) is
shown. It should be understood in advance that the components,
layers, and functions shown in FIG. 3 are intended to be
illustrative only and the disclosure and claims are not limited
thereto. As depicted, the following layers and corresponding
functions are provided.
[0046] Hardware and software layer 310 includes hardware and
software components. Examples of hardware components include
mainframes 352; RISC (Reduced Instruction Set Computer)
architecture based servers 354; servers 356; blade servers 358;
storage devices 360; and networks and networking components 362. In
some embodiments, software components include network application
server software 364 and database software 366.
[0047] Virtualization layer 320 provides an abstraction layer from
which the following examples of virtual entities may be provided:
virtual servers 368; virtual storage 370; virtual networks 372,
including virtual private networks; virtual applications and
operating systems 374; and virtual clients 376.
[0048] In one example, management layer 330 may provide the
functions described below. Resource provisioning 378 provides
dynamic procurement of computing resources and other resources that
are utilized to perform tasks within the cloud computing
environment. Metering and Pricing 380 provide cost tracking as
resources are utilized within the cloud computing environment, and
billing or invoicing for consumption of these resources. In one
example, these resources may comprise application software
licenses. Security provides identity verification for cloud
consumers and tasks, as well as protection for data and other
resources. User portal 382 provides access to the cloud computing
environment for consumers and system administrators. Service level
management 384 provides cloud computing resource allocation and
management such that required service levels are met. Service Level
Agreement (SLA) planning and fulfillment 386 provide
pre-arrangement for, and procurement of, cloud computing resources
for which a future requirement is anticipated in accordance with an
SLA. The management layer further includes an aggressiveness policy
mechanism (APM) 350 as described herein. While the APM 350 is shown
in FIG. 3 to reside in the management layer 330, the APM 350
actually may span other levels shown in FIG. 3 as needed.
[0049] Workloads layer 340 provides examples of functionality for
which the cloud computing environment may be utilized. Examples of
workloads and functions which may be provided from this layer
include: mapping and navigation 386; software development and
lifecycle management 390; virtual classroom education delivery 392;
data analytics processing 394; transaction processing 396 and
mobile desktop 398.
[0050] The present invention may be a system, a method, and/or a
computer program product at any possible technical detail level of
integration. The computer program product may include a computer
readable storage medium (or media) having computer readable program
instructions thereon for causing a processor to carry out aspects
of the present invention.
[0051] The computer readable storage medium can be a tangible
device that can retain and store instructions for use by an
instruction execution device. The computer readable storage medium
may be, for example, but is not limited to, an electronic storage
device, a magnetic storage device, an optical storage device, an
electromagnetic storage device, a semiconductor storage device, or
any suitable combination of the foregoing. A non-exhaustive list of
more specific examples of the computer readable storage medium
includes the following: a portable computer diskette, a hard disk,
a random access memory (RAM), a read-only memory (ROM), an erasable
programmable read-only memory (EPROM or Flash memory), a static
random access memory (SRAM), a portable compact disc read-only
memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a
floppy disk, a mechanically encoded device such as punch-cards or
raised structures in a groove having instructions recorded thereon,
and any suitable combination of the foregoing. A computer readable
storage medium, as used herein, is not to be construed as being
transitory signals per se, such as radio waves or other freely
propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
[0052] Computer readable program instructions described herein can
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
[0053] Computer readable program instructions for carrying out
operations of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, configuration data for integrated
circuitry, or either source code or object code written in any
combination of one or more programming languages, including an
object oriented programming language such as Smalltalk, C++, or the
like, and procedural programming languages, such as the "C"
programming language or similar programming languages. The computer
readable program instructions may execute entirely on the user's
computer, partly on the user's computer, as a stand-alone software
package, partly on the user's computer and partly on a remote
computer or entirely on the remote computer or server. In the
latter scenario, the remote computer may be connected to the user's
computer through any type of network, including a local area
network (LAN) or a wide area network (WAN), or the connection may
be made to an external computer (for example, through the Internet
using an Internet Service Provider). In some embodiments,
electronic circuitry including, for example, programmable logic
circuitry, field-programmable gate arrays (FPGA), or programmable
logic arrays (PLA) may execute the computer readable program
instructions by utilizing state information of the computer
readable program instructions to personalize the electronic
circuitry, in order to perform aspects of the present
invention.
[0054] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer readable
program instructions.
[0055] These computer readable program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing apparatus to
produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in
a computer readable storage medium that can direct a computer, a
programmable data processing apparatus, and/or other devices to
function in a particular manner, such that the computer readable
storage medium having instructions stored therein comprises an
article of manufacture including instructions which implement
aspects of the function/act specified in the flowchart and/or block
diagram block or blocks.
[0056] The computer readable program instructions may also be
loaded onto a computer, other programmable data processing
apparatus, or other device to cause a series of operational steps
to be performed on the computer, other programmable apparatus or
other device to produce a computer implemented process, such that
the instructions which execute on the computer, other programmable
apparatus, or other device implement the functions/acts specified
in the flowchart and/or block diagram block or blocks.
[0057] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the blocks may occur out of the order noted in
the Figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts or carry out combinations
of special purpose hardware and computer instructions.
[0058] Referring now to FIG. 4, a block diagram illustrates a
aggressiveness policy mechanism (APM) 350 that was introduced above
with reference to FIG. 3. The APM 350 dynamically changes
aggressiveness for optimizing placement of virtual machines on
physical hosts. In the illustrated example, the APM 350 is part of
a cloud manager 410. The cloud manager 410 may be similar to cloud
managers known in the prior art but includes the additional
features of the aggressiveness policy mechanism 350 as described
herein. The cloud manager 410 allows a human user or system
administrator 412 to set up and manage computer resources through a
user interface 414. The cloud manager 410 implements the cloud
management functions 330 described above with reference to FIG. 3.
The aggressiveness policy mechanism 350 may be incorporated into
the scheduler (not shown) which manages migration of VMs to
physical hosts as known in the prior art.
[0059] Again referring to FIG. 4, the cloud manager 410 includes an
optimizer 416. The optimizer 416 determines an optimum location for
the placement of virtual machines for load balancing and other
needs of the system. The optimizer 416 may operate similarly to
prior art optimizers except as described herein. The optimizer 416
monitors VM and host performance and allows the scheduler (not
shown) to migrate VMs to other hosts according to optimization
policies 418 set by the system administrator 412. The optimization
policies 418 are policies as known in the prior art to optimize
placement of the virtual machines on hosts 440 in the computer
resources 430.
[0060] Referring again to FIG. 4, the cloud manager 410 allows the
system administrator 412 to set up and manage physical computer
resources 430. Computer resources 430 represent physical computer
resources such as a physical host computer system in a cloud
computing environment. A set of computer resources managed as a
group is sometimes referred to as a "cloud". In the illustrated
example, the computer resources (or cloud) 430 includes one or more
physical computer hosts 440. The physical computer hosts 440 may be
located remotely from the cloud manager. A host is a physical
computer accessible over a network to the cloud manager. A host has
a hypervisor (software) that allows the host to run one or more
virtual machines as known in the prior art. As shown in FIG. 4,
computer resources 430 include one or more hosts 440 which includes
host1 442. In this example, host1 442 has two virtual machines,
namely: VM1 444 and VM2 446.
[0061] As introduced above, the aggressiveness policy mechanism 350
dynamically changes aggressiveness for optimizing placement of
virtual machines on physical hosts. In the illustrated example in
FIG. 4, the aggressiveness policy mechanism (APM) 350 includes
aggressiveness settings 422 and aggressiveness policies 424. The
aggressiveness settings 422 and aggressiveness policies 424 may be
stored in memory with the APM 350 or any memory associated with or
accessible to the cloud manager 410. The APM 350 processes the
aggressiveness policies 424 to set or modify the aggressiveness
settings 422. The aggressiveness settings 422 are used by the
optimizer 416 to determine how aggressively to apply optimization
policies 418 to move virtual machines among the physical hosts 440
of the cloud 430.
[0062] FIG. 5 is a block diagram that that illustrates a simplified
example of dynamically changing the aggressiveness of optimization
for placement of virtual machines on host computers. In this
example, the optimizer 416 has determined to optimize host1 442 by
moving a virtual machine 512 to host2 514 using the optimization
policies 418 (FIG. 4) in the manner known in the prior art. The APM
350 (FIG. 4) provides aggressiveness setting 422 to the optimizer
416 to control the aggressiveness of optimization. In this example,
the aggressiveness settings 422 indicate to the optimizer 416 to
limit movement of virtual machines between hosts to one migration
per hour. The APM 350 processes the aggressiveness policies 424 to
set or modify the aggressiveness settings 422. The aggressiveness
policies 424 indicate how to set the aggressiveness settings 422
depending on system conditions 516 as described further below. The
APM 350 monitors the system conditions 516 to dynamically change
the aggressiveness settings 422 according to the aggressiveness
policies 424. When the aggressiveness policies 424 and changing
system conditions 516 indicate the aggressiveness settings should
be changed, updated aggressiveness settings 422 are sent to the
optimizer 416. The updated aggressiveness settings may then
indicate a new maximum for moving virtual machines between hosts.
For example, the new maximum for moving virtual machine hosts may
be changed to five or ten migrations per hour (not shown) instead
of 1 migration per hour previously.
[0063] The aggressiveness settings 422 described above with
reference to FIG. 4 are determined by the APM 350 using one or more
aggressiveness policies 424 set up by the system administrator 412.
The aggressiveness policies 422 describe an aggressiveness setting
or a change to an aggressiveness setting depending on one or more
system conditions 516 as shown in FIG. 5. Examples of system
conditions that may be used include time based conditions such as
time of the day, day of the week, holidays, etc. Other conditions
that can be used may be related to the loading condition of
hardware and software in the system. For example, these conditions
may include the number of migration failures in the recent past,
the number of network connections for a physical host, the number
of packets dropped on a network connection, number of deployments
in the last N minutes, the total number of virtual machines in the
cloud, and the total number of hosts in the cloud, etc.
[0064] As introduced above, the APM 350 (FIG. 4) sends
aggressiveness setting 422 to the optimizer 416. The aggressiveness
settings 422 may include one or more settings that indicate
restrictions on the optimizer in a given time period or for
concurrent operations. For example, the setting may include a
maximum number of concurrent migrations per host, a maximum number
of concurrent migrations per cloud, a maximum number of migrations
per host per hour, and a maximum number of migrations per cloud per
hour. Thus the aggressiveness of the system or cloud could be
reflected in a 4-tuple as follows:
aggressiveness=max_concurrent_migrations_per_host, [0065]
max_concurrent_migrations_per_cloud, [0066]
max_migrationsper_hourper_host, [0067]
max_migrationsper_hourper_cloud.
[0068] Each of the aggressiveness settings in the 4-tuple above may
have a numerical value such that at one particular time the
aggressiveness settings could be represented as follows:
aggressiveness=10,100,50,1000.
[0069] The aggressiveness policies 424 may be in the form of an
expression or a function that returns a set of values for a number
of aggressiveness settings depending on one or more system or cloud
conditions 510 as shown in FIG. 5. For some examples,
aggressiveness policies may be as follows: [0070] If the time of
day="peak hours" then set the values of the aggressiveness setting
to aggressiveness=5, 50, 25, 500. [0071] If the time of
day="non-peak hours" then set the values of the aggressiveness
setting to aggressiveness=10, 100, 50, 1000. [0072] If the number
of migration failures in the last 2 hours is greater than 1, then
set the values of the aggressiveness setting to aggressiveness=1,
10, 5, 25. [0073] If the number of migration failures in the last 2
hours is zero, then set the values of the aggressiveness setting to
aggressiveness=10, 100, 50, 1000. Alternatively, instead of setting
the aggressiveness settings to a specific value, the aggressiveness
policies may modify the current values of the aggressiveness
settings and set a new value based on the cloud conditions and the
previous aggressiveness settings. For some examples, aggressiveness
policies may be as follows: [0074] If the number of migration
failures in the last 2 hours is greater than 1, then set the values
of the aggressiveness setting to 1/2 of their current value. [0075]
Set the
max_concurrent_migrations_per_host=8-(0.5*number_of_recent_migration_fail-
ures)-(0.05*number_of_recent_vm_deployments) [0076] Set the
max_concurrent_migrations_per_cloud=0.6*max_concurrent_migrations_per_hos-
t*(number_of_hosts+1) [0077] Set the
max_migrations_per_hour_per_host=16+(0.5*number_of_VMs)-(0.25*number_of_r-
ecent_migration_failures) [0078] Set the
max_migrations_per_hour_per_cloud=0.7*max_migrations_per_hour_per_host*(n-
umber_of_hosts+1)
[0079] FIG. 6 illustrates a flow diagram of a method 600 for
dynamic aggressiveness in optimizing placement of virtual machines
on physical hosts. The method 600 is presented as a series of steps
performed by a computer software program such as the aggressiveness
policy mechanism 350 described above. First, get the current
conditions of the cloud (step 610). Get the aggressiveness policies
(step 620). Evaluate the policies using the current conditions in
step 610 to set the aggressiveness settings (step 630). Send
updated aggressiveness settings to the optimizer (step 640).
Optimize loading of the physical hosts with the aggressiveness
settings (step 650). The method is then done.
[0080] Referring now to FIG. 7, a flow diagram shows method 700
that is an exemplary method for performing step 630 in method 600
for dynamically changing aggressiveness in optimizing placement of
virtual machines on physical hosts. The method 700 is presented as
a series of steps performed by a computer software program such as
the aggressiveness policy mechanism 350 described above. First, get
the current date and time (step 710). If there are polices for the
current date and time (step 720=yes) then apply the aggressiveness
polices to update the aggressiveness settings (step 730) and the
method is done. If there are no polices for the current date and
time (step 720=no) then the method is done.
[0081] The claims and disclosure herein provide an apparatus and
method for dynamically changing the aggressiveness in which the
optimizer optimizes placement of virtual machines on physical hosts
to allow more efficient and varied optimization.
[0082] One skilled in the art will appreciate that many variations
are possible within the scope of the claims. Thus, while the
disclosure is particularly shown and described above, it will be
understood by those skilled in the art that these and other changes
in form and details may be made therein without departing from the
spirit and scope of the claims.
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