U.S. patent application number 16/050583 was filed with the patent office on 2018-11-22 for user customizable data processing plan in a dispersed storage network.
The applicant listed for this patent is International Business Machines Corporation. Invention is credited to Kumar Abhijeet, Greg R. Dhuse, S. Christopher Gladwin, Jason K. Resch.
Application Number | 20180335967 16/050583 |
Document ID | / |
Family ID | 64271945 |
Filed Date | 2018-11-22 |
United States Patent
Application |
20180335967 |
Kind Code |
A1 |
Resch; Jason K. ; et
al. |
November 22, 2018 |
USER CUSTOMIZABLE DATA PROCESSING PLAN IN A DISPERSED STORAGE
NETWORK
Abstract
A method includes obtaining, by a user computing device of a
dispersed storage network (DSN), a DSN access request and
determining a custom data processing plan for the DSN access
request. The method further includes identifying two or more
dispersed storage (DS) processing units of the DSN as candidates to
process the DSN access request. The method further includes
determining DS processing capabilities of each of the two or more
DS processing units and selecting a DS processing unit to process
the DSN access request based on a favorable comparison of the DS
processing capabilities and the custom data processing plan. The
method further includes selecting DS processing options of the DS
processing unit to process the DSN access request according to the
custom data processing plan, and sending the DSN access request and
selection of the one or more DS processing options to the DS
processing unit.
Inventors: |
Resch; Jason K.; (Chicago,
IL) ; Gladwin; S. Christopher; (Chicago, IL) ;
Abhijeet; Kumar; (Chicago, IL) ; Dhuse; Greg R.;
(Chicago, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation |
Armonk |
NY |
US |
|
|
Family ID: |
64271945 |
Appl. No.: |
16/050583 |
Filed: |
July 31, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14325433 |
Jul 8, 2014 |
10067831 |
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16050583 |
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12903209 |
Oct 13, 2010 |
9152489 |
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14325433 |
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61290775 |
Dec 29, 2009 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 3/067 20130101;
G06F 11/1092 20130101; G06F 3/0619 20130101; G06F 11/1076 20130101;
G06F 3/0638 20130101; G06F 3/0659 20130101 |
International
Class: |
G06F 3/06 20060101
G06F003/06; G06F 11/10 20060101 G06F011/10 |
Claims
1. A method comprises: obtaining, by a user computing device of a
plurality of user computing devices of a dispersed storage network
(DSN), a DSN access request; determining, by the user computing
device, a custom data processing plan to process the DSN access
request; identifying, by the user computing device, two or more
dispersed storage (DS) processing units of a plurality of DS
processing units of the DSN as possible candidates to process the
DSN access request; determining, by the user computing device, DS
processing capabilities of each of the two or more DS processing
units; selecting, by the user computing device, a DS processing
unit of the two or more DS processing units to process the DSN
access request based on a favorable comparison of the DS processing
capabilities of the DS processing unit and the custom data
processing plan; selecting, by the user computing device, one or
more DS processing options of the DS processing unit to process the
DSN access request according to the custom data processing plan;
and sending, by the user computing device, the DSN access request
and selection of the one or more DS processing options to the DS
processing unit, wherein the DS processing unit processes the DSN
access request in accordance with the one or more DS processing
options.
2. The method of claim 1, wherein the determining the custom data
processing plan includes one or more of: selecting, by the user
computing device, dispersed storage error encoding parameters for
storing data of the DSN access request in accordance with a desired
level of security requirement; selecting, by the user computing
device, the dispersed storage error encoding parameters for storing
the data of the DSN access request in accordance with a desired
level of performance requirement; and selecting, by the user
computing device, the dispersed storage error encoding parameters
for storing the data of the DSN access request in accordance with a
desired level of access requirement.
3. The method of claim 1, wherein the identifying the two or more
DS processing units comprises one or more of: accessing, by the
user computing device, a virtual DSN table that includes, for the
plurality of DS processing units, information regarding
availability and one or more of: a data type, a data size, a DSN
access request processing type, a security indicator, a performance
indicator, and a status indicator; receiving, by the user computing
device, a command identifying the two or more DS processing units;
performing, by the user computing device, a lookup of available DS
processing units of the plurality of DS processing units;
identifying, by user computing device, a predetermined two or more
DS processing units as the two or more DS processing units; and
receiving, by the user computing device, messages from DS
processing units of the plurality of DS processing units in
response to a query-response protocol to obtain the
information.
4. The method of claim 3, wherein the identifying the two or more
DS processing units further comprises: when the information is
obtained, correlating, by the user computing device, the
information regarding the one or more of: the data type, the data
size, the security indicator, the performance indicator, and the
status indicator with the custom data processing plan; and
identifying, by the user computing device, DS processing units
having information that correlates with the custom data processing
plan as the two or more DS processing units.
5. The method of claim 1, wherein the DS processing capabilities
include one or more of: current capacity; current loading; uptime
history; performance history; data types supported; data types not
supported; DSN access requests supported; security restrictions;
and encryption algorithms supported.
6. The method of claim 1, wherein the DS processing options include
one or more of: compression type; encryption type; encoding
function type; and rebuilding options.
7. A user computing device of a plurality of user computing devices
of a dispersed storage network (DSN), the user computing device
comprises: an interface; memory; and a processing module operably
coupled to the memory and the interface, wherein the processing
module is operable to: obtain a DSN access request; determine a
custom data processing plan to process the DSN access request;
identify two or more dispersed storage (DS) processing units of a
plurality of DS processing units of the DSN as possible candidates
to process the DSN access request; determining, by the user
computing device, DS processing capabilities of each of the two or
more DS processing units; select a DS processing unit of the two or
more DS processing units to process the DSN access request based on
a favorable comparison of the DS processing capabilities of the DS
processing unit and the custom data processing plan; select one or
more DS processing options of the DS processing unit to process the
DSN access request according to the custom data processing plan;
and send the DSN access request and selection of the one or more DS
processing options to the DS processing unit, wherein the DS
processing unit processes the DSN access request in accordance with
the one or more DS processing options.
8. The user computing device of claim 7, wherein the processing
module is operable to determine the custom data processing plan by
one or more of: selecting dispersed storage error encoding
parameters for storing data of the DSN access request in accordance
with a desired level of security requirement; selecting the
dispersed storage error encoding parameters for storing the data of
the DSN access request in accordance with a desired level of
performance requirement; and selecting the dispersed storage error
encoding parameters for storing the data of the DSN access request
in accordance with a desired level of access requirement.
9. The user computing device claim 7, wherein the processing module
is operable to identify the two or more DS processing units by one
or more of: accessing a virtual DSN table that includes, for the
plurality of DS processing units, information regarding
availability and one or more of: a data type, a data size, a DSN
access request processing type, a security indicator, a performance
indicator, and a status indicator; receiving a command identifying
the two or more DS processing units; performing a lookup of
available DS processing units of the plurality of DS processing
units; identifying a predetermined two or more DS processing units
as the two or more DS processing units; and receiving messages from
DS processing units of the plurality of DS processing units in
response to a query-response protocol to obtain the
information.
10. The user computing device of claim 9, wherein the processing
module is operable to further identify the two or more DS
processing units by: when the information is obtained, correlating
the information regarding the one or more of: the data type, the
data size, the security indicator, the performance indicator, and
the status indicator with the custom data processing plan; and
identifying DS processing units having information that correlates
with the custom data processing plan as the two or more DS
processing units.
11. The user computing device of claim 7, wherein the DS processing
capabilities include one or more of: current capacity; current
loading; uptime history; performance history; data types supported;
data types not supported; DSN access requests supported; security
restrictions; and encryption algorithms supported.
12. The user computing device of claim 7, wherein the DS processing
options include one or more of: compression type; encryption type;
encoding function type; and rebuilding options.
13. A computer readable memory comprises: a first memory element
that stores operational instructions that, when executed by a user
computing device of a plurality of user computing devices of a
dispersed storage network (DSN), causes the user computing device
to: obtain a DSN access request; determine a custom data processing
plan to process the DSN access request; identify two or more
dispersed storage (DS) processing units of a plurality of DS
processing units of the DSN as possible candidates to process the
DSN access request; determining, by the user computing device, DS
processing capabilities of each of the two or more DS processing
units; select a DS processing unit of the two or more DS processing
units to process the DSN access request based on a favorable
comparison of the DS processing capabilities of the DS processing
unit and the custom data processing plan; select one or more DS
processing options of the DS processing unit to process the DSN
access request according to the custom data processing plan; and
send the DSN access request and selection of the one or more DS
processing options to the DS processing unit, wherein the DS
processing unit processes the DSN access request in accordance with
the one or more DS processing options.
14. The computer readable memory of claim 13, wherein the first
memory element further stores operational instructions that, when
executed by the user computing device, causes the user computing
device to determine the custom data processing plan by one or more
of: selecting dispersed storage error encoding parameters for
storing data of the DSN access request in accordance with a desired
level of security requirement; selecting the dispersed storage
error encoding parameters for storing the data of the DSN access
request in accordance with a desired level of performance
requirement; and selecting the dispersed storage error encoding
parameters for storing the data of the DSN access request in
accordance with a desired level of access requirement.
15. The computer readable memory of claim 13, wherein the first
memory element further stores operational instructions that, when
executed by the user computing device, causes the user computing
device to identify the two or more DS processing units by one or
more of: accessing a virtual DSN table that includes, for the
plurality of DS processing units, information regarding
availability and one or more of: a data type, a data size, a DSN
access request processing type, a security indicator, a performance
indicator, and a status indicator; receiving a command identifying
the two or more DS processing units; performing a lookup of
available DS processing units of the plurality of DS processing
units; identifying a predetermined two or more DS processing units
as the two or more DS processing units; and receiving messages from
DS processing units of the plurality of DS processing units in
response to a query-response protocol to obtain the
information.
16. The computer readable memory of claim 15, wherein the first
memory element further stores operational instructions that, when
executed by the user computing device, causes the user computing
device to further identify the two or more DS processing units by
one or more of: when the information is obtained, correlating the
information regarding the one or more of: the data type, the data
size, the security indicator, the performance indicator, and the
status indicator with the custom data processing plan; and
identifying DS processing units having information that correlates
with the custom data processing plan as the two or more DS
processing units.
17. The computer readable memory of claim 13, wherein the DS
processing capabilities include one or more of: current capacity;
current loading; uptime history; performance history; data types
supported; data types not supported; DSN access requests supported;
security restrictions; and encryption algorithms supported.
18. The computer readable memory of claim 13, wherein the DS
processing options include one or more of: compression type;
encryption type; encoding function type; and rebuilding options.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority pursuant to 35 U.S.C.
.sctn. 120 as a continuation-in-part of U.S. patent application
Ser. No. 14/325,433 entitled "SLICE MIGRATION IN A DISPERSED
STORAGE NETWORK," filed Jul. 8, 2014, which claims priority claims
priority pursuant to 35 U.S.C. .sctn. 120 as a continuation-in-part
of U.S. patent application Ser. No. 12/903,209 entitled, "REVISION
SYNCHRONIZATION OF A DISPERSED STORAGE NETWORK," filed Oct. 13,
2010, issued as U.S. Pat. No. 9,152,489 on Oct. 6, 2015, which
claims priority pursuant to 35 USC .sctn. 119 to U.S. Provisional
Application No. 61/290,775 entitled "DISTRIBUTED STORAGE DATA
SYNCHRONIZATION," filed Dec. 29, 2009, all of which are hereby
incorporated herein by reference in their entirety and made part of
the present U.S. Utility Patent Application for all purposes.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
[0002] Not Applicable.
INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT
DISC
[0003] Not Applicable.
BACKGROUND OF THE INVENTION
Technical Field of the Invention
[0004] This invention relates generally to computer networks and
more particularly to dispersing error encoded data.
Description of Related Art
[0005] Computing devices are known to communicate data, process
data, and/or store data. Such computing devices range from wireless
smart phones, laptops, tablets, personal computers (PC), work
stations, and video game devices, to data centers that support
millions of web searches, stock trades, or on-line purchases every
day. In general, a computing device includes a central processing
unit (CPU), a memory system, user input/output interfaces,
peripheral device interfaces, and an interconnecting bus
structure.
[0006] As is further known, a computer may effectively extend its
CPU by using "cloud computing" to perform one or more computing
functions (e.g., a service, an application, an algorithm, an
arithmetic logic function, etc.) on behalf of the computer.
Further, for large services, applications, and/or functions, cloud
computing may be performed by multiple cloud computing resources in
a distributed manner to improve the response time for completion of
the service, application, and/or function. For example, Hadoop is
an open source software framework that supports distributed
applications enabling application execution by thousands of
computers.
[0007] In addition to cloud computing, a computer may use "cloud
storage" as part of its memory system. As is known, cloud storage
enables a user, via its computer, to store files, applications,
etc. on an Internet storage system. The Internet storage system may
include a RAID (redundant array of independent disks) system and/or
a dispersed storage system that uses an error correction scheme to
encode data for storage.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
[0008] FIG. 1 is a schematic block diagram of an embodiment of a
dispersed or distributed storage network (DSN) in accordance with
the present invention;
[0009] FIG. 2 is a schematic block diagram of an embodiment of a
computing core in accordance with the present invention;
[0010] FIG. 3 is a schematic block diagram of an example of
dispersed storage error encoding of data in accordance with the
present invention;
[0011] FIG. 4 is a schematic block diagram of a generic example of
an error encoding function in accordance with the present
invention;
[0012] FIG. 5 is a schematic block diagram of a specific example of
an error encoding function in accordance with the present
invention;
[0013] FIG. 6 is a schematic block diagram of an example of a slice
name of an encoded data slice (EDS) in accordance with the present
invention;
[0014] FIG. 7 is a schematic block diagram of an example of
dispersed storage error decoding of data in accordance with the
present invention;
[0015] FIG. 8 is a schematic block diagram of a generic example of
an error decoding function in accordance with the present
invention;
[0016] FIG. 9 is a schematic block diagram of an embodiment of the
dispersed or distributed storage network (DSN) in accordance with
the present invention;
[0017] FIG. 10 is a flowchart illustrating an example of selecting
a dispersed storage (DS) processing unit in accordance with the
invention;
[0018] FIG. 11 is a schematic block diagram of another embodiment
of the dispersed or distributed storage network (DSN) in accordance
with the present invention; and
[0019] FIG. 12 is a flowchart illustrating an example of selecting
a dispersed storage (DS) processing unit according to a custom data
processing plan in accordance with the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0020] FIG. 1 is a schematic block diagram of an embodiment of a
dispersed, or distributed, storage network (DSN) 10 that includes a
plurality of computing devices 12-16, a managing unit 18, an
integrity processing unit 20, and a DSN memory 22. The components
of the DSN 10 are coupled to a network 24, which may include one or
more wireless and/or wire lined communication systems; one or more
non-public intranet systems and/or public internet systems; and/or
one or more local area networks (LAN) and/or wide area networks
(WAN).
[0021] The DSN memory 22 includes a plurality of storage units 36
that may be located at geographically different sites (e.g., one in
Chicago, one in Milwaukee, etc.), at a common site, or a
combination thereof. For example, if the DSN memory 22 includes
eight storage units 36, each storage unit is located at a different
site. As another example, if the DSN memory 22 includes eight
storage units 36, all eight storage units are located at the same
site. As yet another example, if the DSN memory 22 includes eight
storage units 36, a first pair of storage units are at a first
common site, a second pair of storage units are at a second common
site, a third pair of storage units are at a third common site, and
a fourth pair of storage units are at a fourth common site. Note
that a DSN memory 22 may include more or less than eight storage
units 36. Further note that each storage unit 36 includes a
computing core (as shown in FIG. 2, or components thereof) and a
plurality of memory devices for storing dispersed error encoded
data.
[0022] Each of the computing devices 12-16, the managing unit 18,
and the integrity processing unit 20 include a computing core 26,
which includes network interfaces 30-33. Computing devices 12-16
may each be a portable computing device and/or a fixed computing
device. A portable computing device may be a social networking
device, a gaming device, a cell phone, a smart phone, a digital
assistant, a digital music player, a digital video player, a laptop
computer, a handheld computer, a tablet, a video game controller,
and/or any other portable device that includes a computing core. A
fixed computing device may be a computer (PC), a computer server, a
cable set-top box, a satellite receiver, a television set, a
printer, a fax machine, home entertainment equipment, a video game
console, and/or any type of home or office computing equipment.
Note that each of the managing unit 18 and the integrity processing
unit 20 may be separate computing devices, may be a common
computing device, and/or may be integrated into one or more of the
computing devices 12-16 and/or into one or more of the storage
units 36.
[0023] Each interface 30, 32, and 33 includes software and hardware
to support one or more communication links via the network 24
indirectly and/or directly. For example, interface 30 supports a
communication link (e.g., wired, wireless, direct, via a LAN, via
the network 24, etc.) between computing devices 14 and 16. As
another example, interface 32 supports communication links (e.g., a
wired connection, a wireless connection, a LAN connection, and/or
any other type of connection to/from the network 24) between
computing devices 12 & 16 and the DSN memory 22. As yet another
example, interface 33 supports a communication link for each of the
managing unit 18 and the integrity processing unit 20 to the
network 24.
[0024] Computing devices 12 and 16 include a dispersed storage (DS)
client module 34, which enables the computing device to dispersed
storage error encode and decode data as subsequently described with
reference to one or more of FIGS. 3-8. In this example embodiment,
computing device 16 functions as a dispersed storage (DS)
processing agent (i.e., a DS processing unit) for computing device
14. In this role, computing device 16 dispersed storage error
encodes and decodes data on behalf of computing device 14. With the
use of dispersed storage error encoding and decoding, the DSN 10 is
tolerant of a significant number of storage unit failures (the
number of failures is based on parameters of the dispersed storage
error encoding function) without loss of data and without the need
for a redundant or backup copies of the data. Further, the DSN 10
stores data for an indefinite period of time without data loss and
in a secure manner (e.g., the system is very resistant to
unauthorized attempts at accessing the data).
[0025] In operation, the managing unit 18 performs DS management
services. For example, the managing unit 18 establishes distributed
data storage parameters (e.g., vault creation, distributed storage
parameters, security parameters, billing information, user profile
information, etc.) for computing devices 12-14 (i.e., user
computing devices 12-14) individually or as part of a group of user
devices. As a specific example, the managing unit 18 coordinates
creation of a vault (e.g., a virtual memory block associated with a
portion of an overall namespace of the DSN) within the DSN memory
22 for a user device, a group of devices, or for public access and
establishes per vault dispersed storage (DS) error encoding
parameters for a vault. The managing unit 18 facilitates storage of
DS error encoding parameters for each vault by updating registry
information of the DSN 10, where the registry information may be
stored in the DSN memory 22, a computing device 12-16, the managing
unit 18, and/or the integrity processing unit 20.
[0026] The DSN managing unit 18 creates and stores user profile
information (e.g., an access control list (ACL)) in local memory
and/or within memory of the DSN memory 22. The user profile
information includes authentication information, permissions,
and/or the security parameters. The security parameters may include
encryption/decryption scheme, one or more encryption keys, key
generation scheme, and/or data encoding/decoding scheme.
[0027] The DSN managing unit 18 creates billing information for a
particular user, a user group, a vault access, public vault access,
etc. For instance, the DSN managing unit 18 tracks the number of
times a user accesses a non-public vault and/or public vaults,
which can be used to generate a per-access billing information. In
another instance, the DSN managing unit 18 tracks the amount of
data stored and/or retrieved by a user device and/or a user group,
which can be used to generate a per-data-amount billing
information.
[0028] As another example, the managing unit 18 performs network
operations, network administration, and/or network maintenance.
Network operations includes authenticating user data allocation
requests (e.g., read and/or write requests), managing creation of
vaults, establishing authentication credentials for user devices,
adding/deleting components (e.g., user devices, storage units,
and/or computing devices with a DS client module 34) to/from the
DSN 10, and/or establishing authentication credentials for the
storage units 36. Network administration includes monitoring
devices and/or units for failures, maintaining vault information,
determining device and/or unit activation status, determining
device and/or unit loading, and/or determining any other system
level operation that affects the performance level of the DSN 10.
Network maintenance includes facilitating replacing, upgrading,
repairing, and/or expanding a device and/or unit of the DSN 10.
[0029] The integrity processing unit 20 performs rebuilding of
`bad` or missing encoded data slices. At a high level, the
integrity processing unit 20 performs rebuilding by periodically
attempting to retrieve/list encoded data slices, and/or slice names
of the encoded data slices, from the DSN memory 22. For retrieved
encoded slices, they are checked for errors due to data corruption,
outdated version, etc. If a slice includes an error, it is flagged
as a `bad` slice. For encoded data slices that were not received
and/or not listed, they are flagged as missing slices. Bad and/or
missing slices are subsequently rebuilt using other retrieved
encoded data slices that are deemed to be good slices to produce
rebuilt slices. The rebuilt slices are stored in the DSN memory
22.
[0030] FIG. 2 is a schematic block diagram of an embodiment of a
computing core 26 that includes a processing module 50, a memory
controller 52, main memory 54, a video graphics processing unit 55,
an input/output (IO) controller 56, a peripheral component
interconnect (PCI) interface 58, an IO interface module 60, at
least one IO device interface module 62, a read only memory (ROM)
basic input output system (BIOS) 64, and one or more memory
interface modules. The one or more memory interface module(s)
includes one or more of a universal serial bus (USB) interface
module 66, a host bus adapter (HBA) interface module 68, a network
interface module 70, a flash interface module 72, a hard drive
interface module 74, and a DSN interface module 76.
[0031] The DSN interface module 76 functions to mimic a
conventional operating system (OS) file system interface (e.g.,
network file system (NFS), flash file system (FFS), disk file
system (DFS), file transfer protocol (FTP), web-based distributed
authoring and versioning (WebDAV), etc.) and/or a block memory
interface (e.g., small computer system interface (SCSI), internet
small computer system interface (iSCSI), etc.). The DSN interface
module 76 and/or the network interface module 70 may function as
one or more of the interface 30-33 of FIG. 1. Note that the IO
device interface module 62 and/or the memory interface modules
66-76 may be collectively or individually referred to as IO
ports.
[0032] FIG. 3 is a schematic block diagram of an example of
dispersed storage error encoding of data. When a computing device
12 or 16 has data to store it disperse storage error encodes the
data in accordance with a dispersed storage error encoding process
based on dispersed storage error encoding parameters. The dispersed
storage error encoding parameters include an encoding function
(e.g., information dispersal algorithm, Reed-Solomon, Cauchy
Reed-Solomon, systematic encoding, non-systematic encoding, on-line
codes, etc.), a data segmenting protocol (e.g., data segment size,
fixed, variable, etc.), and per data segment encoding values. The
per data segment encoding values include a total, or pillar width,
number (T) of encoded data slices per encoding of a data segment
i.e., in a set of encoded data slices); a decode threshold number
(D) of encoded data slices of a set of encoded data slices that are
needed to recover the data segment; a read threshold number (R) of
encoded data slices to indicate a number of encoded data slices per
set to be read from storage for decoding of the data segment;
and/or a write threshold number (W) to indicate a number of encoded
data slices per set that must be accurately stored before the
encoded data segment is deemed to have been properly stored. The
dispersed storage error encoding parameters may further include
slicing information (e.g., the number of encoded data slices that
will be created for each data segment) and/or slice security
information (e.g., per encoded data slice encryption, compression,
integrity checksum, etc.).
[0033] In the present example, Cauchy Reed-Solomon has been
selected as the encoding function (a generic example is shown in
FIG. 4 and a specific example is shown in FIG. 5); the data
segmenting protocol is to divide the data object into fixed sized
data segments; and the per data segment encoding values include: a
pillar width of 5, a decode threshold of 3, a read threshold of 4,
and a write threshold of 4. In accordance with the data segmenting
protocol, the computing device 12 or 16 divides the data (e.g., a
file (e.g., text, video, audio, etc.), a data object, or other data
arrangement) into a plurality of fixed sized data segments (e.g., 1
through Y of a fixed size in range of Kilo-bytes to Tera-bytes or
more). The number of data segments created is dependent of the size
of the data and the data segmenting protocol.
[0034] The computing device 12 or 16 then disperse storage error
encodes a data segment using the selected encoding function (e.g.,
Cauchy Reed-Solomon) to produce a set of encoded data slices. FIG.
4 illustrates a generic Cauchy Reed-Solomon encoding function,
which includes an encoding matrix (EM), a data matrix (DM), and a
coded matrix (CM). The size of the encoding matrix (EM) is
dependent on the pillar width number (T) and the decode threshold
number (D) of selected per data segment encoding values. To produce
the data matrix (DM), the data segment is divided into a plurality
of data blocks and the data blocks are arranged into D number of
rows with Z data blocks per row. Note that Z is a function of the
number of data blocks created from the data segment and the decode
threshold number (D). The coded matrix is produced by matrix
multiplying the data matrix by the encoding matrix.
[0035] FIG. 5 illustrates a specific example of Cauchy Reed-Solomon
encoding with a pillar number (T) of five and decode threshold
number of three. In this example, a first data segment is divided
into twelve data blocks (D1-D12). The coded matrix includes five
rows of coded data blocks, where the first row of X11-X14
corresponds to a first encoded data slice (EDS 1_1), the second row
of X21-X24 corresponds to a second encoded data slice (EDS 2_1),
the third row of X31-X34 corresponds to a third encoded data slice
(EDS 3_1), the fourth row of X41-X44 corresponds to a fourth
encoded data slice (EDS 4_1), and the fifth row of X51-X54
corresponds to a fifth encoded data slice (EDS 5_1). Note that the
second number of the EDS designation corresponds to the data
segment number.
[0036] Returning to the discussion of FIG. 3, the computing device
also creates a slice name (SN) for each encoded data slice (EDS) in
the set of encoded data slices. A typical format for a slice name
60 is shown in FIG. 6. As shown, the slice name (SN) 60 includes a
pillar number of the encoded data slice (e.g., one of 1-T), a data
segment number (e.g., one of 1-Y), a vault identifier (ID), a data
object identifier (ID), and may further include revision level
information of the encoded data slices. The slice name functions
as, at least part of, a DSN address for the encoded data slice for
storage and retrieval from the DSN memory 22.
[0037] As a result of encoding, the computing device 12 or 16
produces a plurality of sets of encoded data slices, which are
provided with their respective slice names to the storage units for
storage. As shown, the first set of encoded data slices includes
EDS 1_1 through EDS 5_1 and the first set of slice names includes
SN 1_1 through SN 5_1 and the last set of encoded data slices
includes EDS 1_Y through EDS 5_Y and the last set of slice names
includes SN 1_Y through SN 5_Y.
[0038] FIG. 7 is a schematic block diagram of an example of
dispersed storage error decoding of a data object that was
dispersed storage error encoded and stored in the example of FIG.
4. In this example, the computing device 12 or 16 retrieves from
the storage units at least the decode threshold number of encoded
data slices per data segment. As a specific example, the computing
device retrieves a read threshold number of encoded data
slices.
[0039] To recover a data segment from a decode threshold number of
encoded data slices, the computing device uses a decoding function
as shown in FIG. 8. As shown, the decoding function is essentially
an inverse of the encoding function of FIG. 4. The coded matrix
includes a decode threshold number of rows (e.g., three in this
example) and the decoding matrix in an inversion of the encoding
matrix that includes the corresponding rows of the coded matrix.
For example, if the coded matrix includes rows 1, 2, and 4, the
encoding matrix is reduced to rows 1, 2, and 4, and then inverted
to produce the decoding matrix.
[0040] FIG. 9 is a schematic block diagram of an embodiment of the
dispersed or distributed storage network (DSN). As illustrated, the
DSN includes a plurality of user devices 1-u (e.g., user computing
devices 12-14 of FIG. 1), a plurality of DS processing units 1-p
(e.g., computing device 16 of FIG. 1), and a DSN memory 22. In an
example of operation, the user device 1 may determine a DS
processing unit 3 to utilize based on matching DS processing unit
attributes to DS processing unit requirements. In another example,
user device 2 determines to utilize DS processing unit 3 when DS
processing unit 3 has the most favorable availability history of
the plurality of DS processing units 1-p and DS processing unit 3
is expected to continue to be available at a level that compares
favorably with the user device 2 DS processing unit
requirements.
[0041] In another example of operation, the user device 6 may
determine a DS processing unit 5 to utilize based on a
predetermination and/or initially on a predetermination followed by
a potential subsequent modification based in part on actual
performance. In another example, user device 3 determines to
initially utilize DS processing unit 1 when DS processing unit 1 is
listed in a predetermined table. Next, user device 3 determines to
subsequently utilize DS processing unit 2 when DS processing unit 1
does not perform to a required level and DS processing unit 2 is
the second choice.
[0042] In an example of operation, user device 7 provides DSN
memory access authorization credentials when accessing the DSN
memory 22 via DS processing unit 10. Next, the DS processing unit
10 verifies the authorization credentials. The DS processing unit
10 forwards a DSN memory access request to the DSN memory 22 when
the authorization credential verification is favorable (e.g., on a
list of authorized users for the particular item in the DSN memory
22). The DS processing unit 10 does not forward a DSN memory access
request to the DSN memory 22 when the authorization credential
verification is not favorable (e.g., not on a list of authorized
users for the particular item in the DSN memory 22). The method of
operation of the user device 1-u to determine the DS processing
unit 1-p is discussed in greater detail with reference to FIG.
10.
[0043] In another example, DS processing unit 3 forwards the
authorization credentials to the DSN memory 22 with the DSN memory
access request (e.g., without verification by the DS processing
unit 3). The DSN memory 22 verifies the authorization credentials.
The DSN memory 22 processes the memory access request when the
authorization credential verification is favorable. The DSN memory
22 does not process the memory access request when the
authorization credential verification is not favorable.
[0044] FIG. 10 is a flowchart illustrating an example of selecting
a dispersed storage (DS) processing unit. The method begins at step
82 where a processing module (e.g., of a user device) determines
dispersed storage network (DSN) memory access requirements. The
requirements may include one or more of security requirements,
performance requirements, and priority requirements. Such a
determination may be based on one or more of a query, a data type,
a data size, a security indicator, a performance indicator, a
command, a predetermination, and a lookup.
[0045] The method continues at step 84 where the processing module
determines candidate DS processing units based on one or more of a
virtual DSN address to physical location table, a query, a message
from one or more DS processing units, a data type, a data size, a
security indicator, a performance indicator, a status indicator, a
command, a predetermination, and a lookup. The method continues at
step 86 where the processing module determines candidate DS
processing units attributes where the attributes may include one or
more of current capacity, current loading, uptime history,
performance history, data types supported, data types not
supported, security restrictions, and encryption algorithms
supported. Such a determination may be based on one or more of a
virtual DSN address to physical location table, a query, a message
from one or more DS processing units, a data type, a data size, a
security indicator, a performance indicator, a command, a
predetermination, and a lookup. In an example, the processing
module determines that DS processing unit 1 has an attribute of
capacity above a threshold based on the performance indicator. In
another example, the processing module determines that DS
processing unit 4 has an attribute of a particular encryption
algorithm based on the security indicator from a query.
[0046] The method continues at step 88 where the processing module
determines a DS processing unit to utilize based on one or more of
the DSN access requirements, the candidate DS processing units, the
candidate processing units attributes, a comparison of the
candidate processing units attributes to the DSN access
requirements, a virtual DSN address to physical location table, a
query, a message from one or more DS processing units, a data type,
a data size, a security indicator, a performance indicator, a
command, a predetermination, and a lookup. In an example, the
processing module determines the DS processing unit such that
substantially all of the requirements are met or exceeded. For
instance, the processing module determines the DS processing unit
that meets or exceeds the most requirements. The method continues
at step 90 where the processing module utilizes the determined DS
processing unit for the DSN access (e.g., store, retrieve, delete,
check status).
[0047] FIG. 11 is a schematic block diagram of another embodiment
of the dispersed or distributed storage network (DSN) that includes
a plurality of user computing devices 1-n (e.g., user computing
devices 12-14 of FIG. 1), a plurality of DS processing units 1-x
(e.g., computing device 16 of FIG. 1), and a DSN memory 22.
[0048] In an example of operation, a user computing device of the
user computing devices 1-n obtains a DSN access request (e.g., a
request to store, retrieve, delete, check status, integrity check,
etc., data to/from the DSN memory 22). For example user computing
device 1 obtains DSN access request 1, user computing device 2
obtains DSN access request 2, user computing device 3 obtains DSN
access request 3, and user computing device n obtains DSN access
request n. The user computing device determines a custom data
processing plan to process the DSN access request. The user
computing device determines the custom data processing plan by
selecting dispersed storage error encoding parameters for storing
data of the DSN access request in accordance with a desired level
of security requirement (e.g., for a higher desired level of
security, per encoded data slice encryption, compression, and/or
integrity checksums are selected), selecting dispersed storage
error encoding parameters for storing data of the DSN access
request in accordance with a desired level of performance
requirement (e.g., for a fast read/write DSN access request, a
small decode threshold is selected and for a long term store with
slow write/read (i.e., archive) a larger decode threshold is
selected), and/or selecting dispersed storage error encoding
parameters for storing data of the DSN access request in accordance
with a desired level of access requirement (e.g., if high frequency
reading/writing of data of the DSN access request is expected, a
smaller decode threshold number is selected).
[0049] For example, DSN access request 1 may be a request to write
high definition (HD) video with moderate security, high
performance, and high frequency of access. User computing device 1
determines a custom data processing plan that includes error
encoding parameters for storing data of DSN access request 1 in
accordance with a moderate level of security (e.g., per encoded
data slice encryption and compression are selected), error encoding
parameters for storing data of DSN access request 1 in accordance
with high performance (e.g., a small decode threshold is selected),
and error encoding parameters for storing data of DSN access
request 1 in accordance with high frequency of access (e.g., a
small decode threshold number is selected).
[0050] The custom data processing plan may also include user
selected custom rebuild options. For example, the custom data
processing plan may indicate that after x number of years,
rebuilding of data is no longer required. As another example, the
custom data processing plan may indicate that rebuilding should
occur only if two or more encoded data slices require
rebuilding.
[0051] The user computing device identifies two or more (DS)
processing units of DS processing units 1-x of the DSN as possible
candidates to process the DSN access request. The user computing
device may identify the two or more DS processing units by
accessing a virtual DSN table that includes, for the DS processing
units 1-x, information regarding availability and one or more of: a
data type, a data size, a security indicator, a performance
indicator, and a status indicator. Alternatively, or additionally,
the user computing device may identify the two or more DS
processing units by receiving a command (e.g., a user input)
identifying the two or more DS processing units, performing a
lookup of available DS processing units of the plurality of DS
processing units, identifying a predetermined two or more DS
processing units as the two or more DS processing units, and/or
receiving messages from DS processing units of the plurality of DS
processing units 1-x in response to a query-response protocol to
obtain the information.
[0052] When the information is obtained, (e.g., via accessing a DSN
table and/or querying the DS processing units 1-x) the user
computing device correlates the information regarding the one or
more of: the data type, the data size, the security indicator, the
performance indicator, and the status indicator with the custom
data processing plan. The user computing device can then identify
the two or more DS processing units that are not only available to
process the DSN access request, but have information that
correlates with the custom data processing plan.
[0053] For example, user computing device 1 accesses a virtual DSN
table and identifies DS processing unit 1, DS processing unit 2,
and DS processing unit x as available to process DSN access request
1. The virtual DSN table also indicates information that DS
processing unit x processes low resolution (res) video and photos.
Because this information does not correlate with user computing
device 1's custom data processing plan (i.e., to process HD video),
DS processing unit x is eliminated as a candidate and DS processing
unit 1 and DS processing unit 2 are left as options.
[0054] The user computing device determines DS processing
capabilities of each of the two or more DS processing units
identified as candidates. The DS processing capabilities include
one or more of current capacity, current loading, uptime history,
performance history, data types supported (e.g., high definition
(HD) and above video, low resolution video, etc.), data types not
supported, DSN access requests supported (e.g., the DS processing
unit is a dedicated write or read unit), security restrictions, and
encryption algorithms supported.
[0055] For example, user computing device 1 determines that DS
processing unit 1 has DS processing capabilities of processing HD
and above video and DS processing unit 2 has DS processing
capabilities to perform short term fast stores and reads. However,
DS processing unit 2 has a history of low performance and does not
support processing of HD video.
[0056] The user computing device selects a DS processing unit of
the two or more DS processing units to process the DSN access
request based on a favorable comparison of the DS processing
capabilities of the DS processing unit and the custom data
processing plan. For example, while DS processing unit 2 has DS
processing capabilities to process short term fast stores and reads
which compares favorably to computing device 1's custom data
processing plan, DS processing unit 2's DS processing capabilities
also indicate that it does not process HD video and that it has a
history of poor performance. Therefore, user computing device 1
selects DS processing unit 1 to process DSN access request 1
because DS processing unit 1's DS processing capabilities compare
most favorably to user computing device 1's custom data processing
plan.
[0057] The user computing device selects one or more DS processing
options of the DS processing unit to process the DSN access request
according to the custom data processing plan. The one or more one
or more DS processing options include one or more of a compression
type, encryption type, encoding function type (e.g., IDA type), and
rebuilding options. For example, user computing device 1's custom
data processing plan indicates a high security level, high
performance, and high frequency of access. Therefore, user
computing device 1 selects DS processing options of DS processing
unit 1 according to those requirements.
[0058] The user computing device sends the DSN access request and
selection of the one or more DS processing options to the DS
processing unit, where the DS processing unit processes the DSN
access request in accordance with the one or more DS processing
options.
[0059] FIG. 12 is a flowchart illustrating an example of selecting
a dispersed storage (DS) processing unit according to a custom data
processing plan. The method begins with step 92 where the a user
computing device of a plurality of user computing devices of the
DSN obtains a DSN access request (e.g., a request to store,
retrieve, delete, check status, integrity check, etc., data to/from
the DSN memory 22). The method continues with step 94 where the
user computing device determines a custom data processing plan to
process the DSN access request. The user computing device
determines the custom data processing plan by selecting dispersed
storage error encoding parameters for storing data of the DSN
access request in accordance with a desired level of security
requirement (e.g., for a higher desired level of security, per
encoded data slice encryption, compression, and/or integrity
checksums are selected), selecting dispersed storage error encoding
parameters for storing data of the DSN access request in accordance
with a desired level of performance requirement (e.g., for a fast
read/write DSN access request, a small decode threshold is selected
and for a long term store with slow write/read (i.e., archive) a
larger decode threshold is selected), and/or selecting dispersed
storage error encoding parameters for storing data of the DSN
access request in accordance with a desired level of access
requirement (e.g., if high frequency reading/writing of data of the
DSN access request is expected, a smaller decode threshold number
is selected).
[0060] The custom data processing plan may also include user
selected custom rebuild options. For example, the custom data
processing plan may indicate that after x number of years,
rebuilding of data is no longer required. As another example, the
custom data processing plan may indicate that rebuilding should
occur only if two or more encoded data slices require
rebuilding.
[0061] The method continues with step 96 where the user computing
device identifies two or more (DS) processing units of a plurality
of DS processing units of the DSN as possible candidates to process
the DSN access request. The user computing device may identify the
two or more DS processing units by accessing a virtual DSN table
that includes, for the plurality of DS processing units,
information regarding availability and one or more of: a data type,
a data size, a security indicator, a performance indicator, and a
status indicator. Alternatively, or additionally, the user
computing device may identify the two or more DS processing units
by receiving a command (e.g., a user input) identifying the two or
more DS processing units, performing a lookup of available DS
processing units of the plurality of DS processing units,
identifying a predetermined two or more DS processing units as the
two or more DS processing units, and/or receiving messages from DS
processing units of the plurality of DS processing units in
response to a query-response protocol to obtain the
information.
[0062] When the information is obtained, (e.g., via accessing a DSN
table and/or querying the plurality of DS processing units) the
user computing device correlates the information regarding the one
or more of: the data type, the data size, the security indicator,
the performance indicator, and the status indicator with the custom
data processing plan. The user computing device can then identify
the two or more DS processing units that are not only available to
process the DSN access request, but have information that
correlates with the custom data processing plan.
[0063] The method continues with step 98 where the user computing
device determines DS processing capabilities of each of the two or
more DS processing units identified as candidates. The DS
processing capabilities include one or more of current capacity,
current loading, uptime history, performance history, data types
supported (e.g., high definition (HD) and above video, low
resolution video, etc.), data types not supported, DSN access
requests supported (e.g., the DS processing unit is a dedicated
write or read unit), security restrictions, and encryption
algorithms supported.
[0064] The method continues with step 100 where the user computing
device selects a DS processing unit of the two or more DS
processing units to process the DSN access request based on a
favorable comparison of the DS processing capabilities of the DS
processing unit and the custom data processing plan. The method
continues with step 102 where the user computing device selects one
or more DS processing options of the DS processing unit to process
the DSN access request according to the custom data processing
plan. The one or more one or more DS processing options include one
or more of a compression type, encryption type, encoding function
type (e.g., IDA type), and rebuilding options.
[0065] The method continues with step 102 where the user computing
device sends the DSN access request and selection of the one or
more DS processing options to the DS processing unit, where the DS
processing unit processes the DSN access request in accordance with
the one or more DS processing options.
[0066] It is noted that terminologies as may be used herein such as
bit stream, stream, signal sequence, etc. (or their equivalents)
have been used interchangeably to describe digital information
whose content corresponds to any of a number of desired types
(e.g., data, video, speech, text, graphics, audio, etc. any of
which may generally be referred to as `data`).
[0067] As may be used herein, the terms "substantially" and
"approximately" provides an industry-accepted tolerance for its
corresponding term and/or relativity between items. For some
industries, an industry-accepted tolerance is less than one percent
and, for other industries, the industry-accepted tolerance is 10
percent or more. Other examples of industry-accepted tolerance
range from less than one percent to fifty percent.
Industry-accepted tolerances correspond to, but are not limited to,
component values, integrated circuit process variations,
temperature variations, rise and fall times, thermal noise,
dimensions, signaling errors, dropped packets, temperatures,
pressures, material compositions, and/or performance metrics.
Within an industry, tolerance variances of accepted tolerances may
be more or less than a percentage level (e.g., dimension tolerance
of less than +/-1%). Some relativity between items may range from a
difference of less than a percentage level to a few percent. Other
relativity between items may range from a difference of a few
percent to magnitude of differences.
[0068] As may also be used herein, the term(s) "configured to",
"operably coupled to", "coupled to", and/or "coupling" includes
direct coupling between items and/or indirect coupling between
items via an intervening item (e.g., an item includes, but is not
limited to, a component, an element, a circuit, and/or a module)
where, for an example of indirect coupling, the intervening item
does not modify the information of a signal but may adjust its
current level, voltage level, and/or power level. As may further be
used herein, inferred coupling (i.e., where one element is coupled
to another element by inference) includes direct and indirect
coupling between two items in the same manner as "coupled to".
[0069] As may even further be used herein, the term "configured
to", "operable to", "coupled to", or "operably coupled to"
indicates that an item includes one or more of power connections,
input(s), output(s), etc., to perform, when activated, one or more
its corresponding functions and may further include inferred
coupling to one or more other items. As may still further be used
herein, the term "associated with", includes direct and/or indirect
coupling of separate items and/or one item being embedded within
another item.
[0070] As may be used herein, the term "compares favorably",
indicates that a comparison between two or more items, signals,
etc., provides a desired relationship. For example, when the
desired relationship is that signal 1 has a greater magnitude than
signal 2, a favorable comparison may be achieved when the magnitude
of signal 1 is greater than that of signal 2 or when the magnitude
of signal 2 is less than that of signal 1. As may be used herein,
the term "compares unfavorably", indicates that a comparison
between two or more items, signals, etc., fails to provide the
desired relationship.
[0071] As may be used herein, one or more claims may include, in a
specific form of this generic form, the phrase "at least one of a,
b, and c" or of this generic form "at least one of a, b, or c",
with more or less elements than "a", "b", and "c". In either
phrasing, the phrases are to be interpreted identically. In
particular, "at least one of a, b, and c" is equivalent to "at
least one of a, b, or c" and shall mean a, b, and/or c. As an
example, it means: "a" only, "b" only, "c" only, "a" and "b", "a"
and "c", "b" and "c", and/or "a", "b", and "c".
[0072] As may also be used herein, the terms "processing module",
"processing circuit", "processor", "processing circuitry", and/or
"processing unit" may be a single processing device or a plurality
of processing devices. Such a processing device may be a
microprocessor, micro-controller, digital signal processor,
microcomputer, central processing unit, field programmable gate
array, programmable logic device, state machine, logic circuitry,
analog circuitry, digital circuitry, and/or any device that
manipulates signals (analog and/or digital) based on hard coding of
the circuitry and/or operational instructions. The processing
module, module, processing circuit, processing circuitry, and/or
processing unit may be, or further include, memory and/or an
integrated memory element, which may be a single memory device, a
plurality of memory devices, and/or embedded circuitry of another
processing module, module, processing circuit, processing
circuitry, and/or processing unit. Such a memory device may be a
read-only memory, random access memory, volatile memory,
non-volatile memory, static memory, dynamic memory, flash memory,
cache memory, and/or any device that stores digital information.
Note that if the processing module, module, processing circuit,
processing circuitry, and/or processing unit includes more than one
processing device, the processing devices may be centrally located
(e.g., directly coupled together via a wired and/or wireless bus
structure) or may be distributedly located (e.g., cloud computing
via indirect coupling via a local area network and/or a wide area
network). Further note that if the processing module, module,
processing circuit, processing circuitry and/or processing unit
implements one or more of its functions via a state machine, analog
circuitry, digital circuitry, and/or logic circuitry, the memory
and/or memory element storing the corresponding operational
instructions may be embedded within, or external to, the circuitry
comprising the state machine, analog circuitry, digital circuitry,
and/or logic circuitry. Still further note that, the memory element
may store, and the processing module, module, processing circuit,
processing circuitry and/or processing unit executes, hard coded
and/or operational instructions corresponding to at least some of
the steps and/or functions illustrated in one or more of the
Figures. Such a memory device or memory element can be included in
an article of manufacture.
[0073] One or more embodiments have been described above with the
aid of method steps illustrating the performance of specified
functions and relationships thereof. The boundaries and sequence of
these functional building blocks and method steps have been
arbitrarily defined herein for convenience of description.
Alternate boundaries and sequences can be defined so long as the
specified functions and relationships are appropriately performed.
Any such alternate boundaries or sequences are thus within the
scope and spirit of the claims. Further, the boundaries of these
functional building blocks have been arbitrarily defined for
convenience of description. Alternate boundaries could be defined
as long as the certain significant functions are appropriately
performed. Similarly, flow diagram blocks may also have been
arbitrarily defined herein to illustrate certain significant
functionality.
[0074] To the extent used, the flow diagram block boundaries and
sequence could have been defined otherwise and still perform the
certain significant functionality. Such alternate definitions of
both functional building blocks and flow diagram blocks and
sequences are thus within the scope and spirit of the claims. One
of average skill in the art will also recognize that the functional
building blocks, and other illustrative blocks, modules and
components herein, can be implemented as illustrated or by discrete
components, application specific integrated circuits, processors
executing appropriate software and the like or any combination
thereof.
[0075] In addition, a flow diagram may include a "start" and/or
"continue" indication. The "start" and "continue" indications
reflect that the steps presented can optionally be incorporated in
or otherwise used in conjunction with one or more other routines.
In addition, a flow diagram may include an "end" and/or "continue"
indication. The "end" and/or "continue" indications reflect that
the steps presented can end as described and shown or optionally be
incorporated in or otherwise used in conjunction with one or more
other routines. In this context, "start" indicates the beginning of
the first step presented and may be preceded by other activities
not specifically shown. Further, the "continue" indication reflects
that the steps presented may be performed multiple times and/or may
be succeeded by other activities not specifically shown. Further,
while a flow diagram indicates a particular ordering of steps,
other orderings are likewise possible provided that the principles
of causality are maintained.
[0076] The one or more embodiments are used herein to illustrate
one or more aspects, one or more features, one or more concepts,
and/or one or more examples. A physical embodiment of an apparatus,
an article of manufacture, a machine, and/or of a process may
include one or more of the aspects, features, concepts, examples,
etc. described with reference to one or more of the embodiments
discussed herein. Further, from figure to figure, the embodiments
may incorporate the same or similarly named functions, steps,
modules, etc. that may use the same or different reference numbers
and, as such, the functions, steps, modules, etc. may be the same
or similar functions, steps, modules, etc. or different ones.
[0077] While the transistors in the above described figure(s)
is/are shown as field effect transistors (FETs), as one of ordinary
skill in the art will appreciate, the transistors may be
implemented using any type of transistor structure including, but
not limited to, bipolar, metal oxide semiconductor field effect
transistors (MOSFET), N-well transistors, P-well transistors,
enhancement mode, depletion mode, and zero voltage threshold (VT)
transistors.
[0078] Unless specifically stated to the contra, signals to, from,
and/or between elements in a figure of any of the figures presented
herein may be analog or digital, continuous time or discrete time,
and single-ended or differential. For instance, if a signal path is
shown as a single-ended path, it also represents a differential
signal path. Similarly, if a signal path is shown as a differential
path, it also represents a single-ended signal path. While one or
more particular architectures are described herein, other
architectures can likewise be implemented that use one or more data
buses not expressly shown, direct connectivity between elements,
and/or indirect coupling between other elements as recognized by
one of average skill in the art.
[0079] The term "module" is used in the description of one or more
of the embodiments. A module implements one or more functions via a
device such as a processor or other processing device or other
hardware that may include or operate in association with a memory
that stores operational instructions. A module may operate
independently and/or in conjunction with software and/or firmware.
As also used herein, a module may contain one or more sub-modules,
each of which may be one or more modules.
[0080] As may further be used herein, a computer readable memory
includes one or more memory elements. A memory element may be a
separate memory device, multiple memory devices, or a set of memory
locations within a memory device. Such a memory device may be a
read-only memory, random access memory, volatile memory,
non-volatile memory, static memory, dynamic memory, flash memory,
cache memory, and/or any device that stores digital information.
The memory device may be in a form a solid-state memory, a hard
drive memory, cloud memory, thumb drive, server memory, computing
device memory, and/or other physical medium for storing digital
information.
[0081] While particular combinations of various functions and
features of the one or more embodiments have been expressly
described herein, other combinations of these features and
functions are likewise possible. The present disclosure is not
limited by the particular examples disclosed herein and expressly
incorporates these other combinations.
* * * * *