U.S. patent application number 16/197235 was filed with the patent office on 2019-03-21 for compressing a slice name listing in a dispersed storage network.
The applicant listed for this patent is International Business Machines Corporation. Invention is credited to Andrew D. Baptist, Wesley B. Leggette, Jason K. Resch, Ilya Volvovski.
Application Number | 20190087599 16/197235 |
Document ID | / |
Family ID | 65719397 |
Filed Date | 2019-03-21 |
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United States Patent
Application |
20190087599 |
Kind Code |
A1 |
Resch; Jason K. ; et
al. |
March 21, 2019 |
COMPRESSING A SLICE NAME LISTING IN A DISPERSED STORAGE NETWORK
Abstract
A method begins by receiving a list range request for a
plurality of slice names within a slice name range. The method
continues with identifying slice names of the plurality of slice
names within the slice name range. The method continues with
determining a representation structure for a list range response.
The method continues with generating, in accordance with the
representation structure, a first portion of a list range response
for a first slice name, where the first portion includes a first
representation of the first slice name. The method continues with
generating, in accordance with the representation structure, one or
more subsequent portions of the list range response for remaining
slice names of the slice names, where the one or more subsequent
portions includes one or more representations of the remaining
slices names. The method continues with sending the list range
response to a requesting device.
Inventors: |
Resch; Jason K.; (Chicago,
IL) ; Baptist; Andrew D.; (Mt. Pleasant, WI) ;
Volvovski; Ilya; (Chicago, IL) ; Leggette; Wesley
B.; (Chicago, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation |
Armonk |
NY |
US |
|
|
Family ID: |
65719397 |
Appl. No.: |
16/197235 |
Filed: |
November 20, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15721093 |
Sep 29, 2017 |
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16197235 |
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14610220 |
Jan 30, 2015 |
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15721093 |
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61974142 |
Apr 2, 2014 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 3/067 20130101;
G06F 21/6254 20130101; G06F 21/6281 20130101; G06F 2221/2141
20130101; G06F 11/00 20130101; G06F 21/6272 20130101; H04L 63/12
20130101; G06F 21/6218 20130101; H04L 67/1097 20130101; H04L 63/20
20130101; H04L 63/104 20130101; H04L 63/101 20130101; H04L 63/0823
20130101 |
International
Class: |
G06F 21/62 20130101
G06F021/62; H04L 29/08 20060101 H04L029/08; H04L 29/06 20060101
H04L029/06 |
Claims
1. A method for execution by a storage unit of a dispersed storage
network (DSN) comprises: receiving, from a requesting device, a
list range request for a plurality of slice names within a slice
name range, wherein the plurality of slice names are associated
with a plurality of encoded data slices stored in the storage unit,
wherein data is dispersed storage error encoded into pluralities of
sets of encoded data slices and stored in storage units of the DSN,
wherein the dispersed storage error encoding is in accordance with
dispersed data storage parameters, wherein the pluralities of sets
of encoded data slices include the plurality of encoded data
slices; identifying slice names of the plurality of slice names
within the slice name range; determining a representation structure
for a list range response; generating, in accordance with the
representation structure, a first portion of a list range response
for a first slice name of the slice names, wherein the first
portion includes a first representation of the first slice name;
generating, in accordance with the representation structure, one or
more subsequent portions of the list range response for remaining
slice names of the slice names, wherein the one or more subsequent
portions includes one or more representations of the remaining
slices names; and sending the list range response to the requesting
device.
2. The method of claim 1, wherein the first representation includes
one of: the first slice name; a result based on performing a
deterministic function on the first slice name; and a truncated
version of the first slice name.
3. The method of claim 1, wherein a representation of the one or
more representations includes one of: an offset from the first
slice name; a result based on a deterministic function applied to
the first slice name and a remaining slice name of the remaining
slice names; a result based on a number of slice names within a
contiguous range of slice names of the remaining slice names; and a
last slice name of the slice names.
4. The method of claim 1, wherein the first portion further
includes a slice revision count field, wherein the slice revision
count field includes one or more of: one or more slice revision
fields; and one or more corresponding slice length fields.
5. The method of claim 1, wherein the one or more subsequent
portions each further include a slice revision count field, wherein
the slice revision count field includes one or more of: one or more
slice revision fields; and one or more corresponding slice length
fields.
6. The method of claim 1, wherein the list range response further
includes one or more of: a request number; a payload length; a
first slice name; and a last slice name.
7. The method of claim 1 further comprises: generating, in
accordance with the representation structure, for a last slice name
of the slice names, a last portion of the list range response.
8. The method of claim 1, wherein the representation structure
includes one or more of: an offset representation; a first slice
name representation; a last slice name representation; a
deterministic function representation; a missing encoded data slice
representation; a contiguous grouping of encoded data slices
representation; and a revision representation.
9. The method of claim 1, wherein the list range request includes
the representation structure.
10. A storage unit of a dispersed storage network (DSN) comprises:
memory; an interface; and a processing module operably coupled to
the memory and the interface, wherein the processing module is
operable to: receive, via the interface and from a requesting
device, a list range request for a plurality of slice names within
a slice name range, wherein the plurality of slice names are
associated with a plurality of encoded data slices stored in the
storage unit, wherein data is dispersed storage error encoded into
pluralities of sets of encoded data slices and stored in storage
units of the DSN, wherein the dispersed storage error encoding is
in accordance with dispersed data storage parameters, wherein the
pluralities of sets of encoded data slices include the plurality of
encoded data slices; identify slice names of the plurality of slice
names within the slice name range; determine a representation
structure for a list range response; generate, in accordance with
the representation structure, a first portion of a list range
response for a first slice name of the slice names, wherein the
first portion includes a first representation of the first slice
name; generate, in accordance with the representation structure,
one or more subsequent portions of the list range response for
remaining slice names of the slice names, wherein the one or more
subsequent portions includes one or more representations of the
remaining slices names; and send, via the interface, the list range
response to the requesting device.
11. The storage unit of claim 10, wherein the processing module is
operable to generate the first representation to include one of:
the first slice name; a result based on performing a deterministic
function on the first slice name; and a truncated version of the
first slice name.
12. The storage unit of claim 10, wherein processing module is
operable to generate a representation of the one or more
representations to include one or more of: an offset from the first
slice name; a result based on a deterministic function applied to
the first slice name and a remaining slice name of the remaining
slice names; a result based on a number of slice names within a
contiguous range of slice names of the remaining slice names; and a
last slice name of the slice names.
13. The storage unit of claim 10, wherein the processing module is
operable to generate the first portion to further include a slice
revision count field, wherein the slice revision count field
includes one or more of: one or more slice revision fields; and one
or more corresponding slice length fields.
14. The storage unit of claim 10, wherein the processing module is
further operable to generate the one or more subsequent portions to
each further include a slice revision count field, wherein the
slice revision count field includes one or more of: one or more
slice revision fields; and one or more corresponding slice length
fields.
15. The storage unit of claim 10, wherein the processing module is
operable to generate the list range response to include one or more
of: a request number; a payload length; a first slice name; and a
last slice name.
16. The storage unit of claim 10, wherein the processing module is
further operable to: generating, in accordance with the
representation structure, for a last slice name of the slice names,
a last portion of the list range response.
17. The storage unit of claim 10, wherein the representation
structure includes one or more of: an offset representation; a
first slice name representation; a last slice name representation;
a deterministic function representation; a missing encoded data
slice representation; a contiguous grouping of encoded data slices
representation; and a revision representation.
18. The storage unit of claim 10, wherein the list range request
includes the representation structure.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present U.S. Utility Patent Application claims priority
pursuant to 35 U. S.C. .sctn. 120 as a continuation-in-part of U.S.
Utility application Ser. No. 15/721,093, entitled "DISTRIBUTING
REGISTRY INFORMATION IN A DISPERSED STORAGE NETWORK", filed Sep.
27, 2017, which is a continuation of U.S. Utility application Ser.
No. 14/610,220, entitled "DISTRIBUTING REGISTRY INFORMATION IN A
DISPERSED STORAGE NETWORK", filed Jan. 30, 2015, which claims
priority pursuant to 35 U.S.C. .sctn. 119(e) to U.S. Provisional
Application No. 61/974,142, entitled "SCHEDULING REBUILDING OF
STORED DATA IN A DISPERSED STORAGE NETWORK", filed Apr. 02, 2014,
expired, 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 identifying dispersed 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 example of
identifying stored encoded data slices in accordance with the
present invention;
[0017] FIG. 10 is a logic diagram of an example of a method of
identifying stored encoded data slices in accordance with the
present invention;
[0018] FIGS. 11A-11D are schematic block diagrams of examples of
list range responses in accordance with the present invention;
and
[0019] FIG. 12 is a logic diagram of an example of a method of
listing stored encoded data slices in accordance with the present
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 40 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
processing agent 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 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 DSTN 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 DSTN 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 DSTN 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 DSTN 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
80 is shown in FIG. 6. As shown, the slice name (SN) 80 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 another embodiment of
a dispersed storage network (DSN) that includes a rebuilding module
90, the network 24 of FIG. 1, and the storage unit 36 of FIG. 1.
The rebuilding module 90 may be implemented by one of a computing
device 12 or 16, a managing unit 18, and a integrity processing
unit 20 of FIG. 1. The storage unit 36 includes the memory 88. The
DSN functions to efficiently identify encoded data slices stored in
the memory 88.
[0041] In an example of operation of the identifying of the encoded
data slices stored in the memory 88, the rebuilding module 90
issues, via the network 24, a list range request 1 that identifies
a start slice name range and an end slice name range. The encoded
data slices stored in the memory 88 are associated with slice
names. The storage unit 36 is associated with a stored slice name
range, where the stored slice name range includes slice names of
the stored encoded data slices. The stored slice name range
includes a range of the list range request. For example, the start
slice name range and the end slice name range fall within the
stored slice name range.
[0042] The storage unit 36 receives the list range request 1.
Having received the list range request 1, the storage unit 36
identifies slice names 80 associated with stored encoded data
slices corresponding to the list range request 1. For example, the
storage unit 36 identifies slices A-1-1, A-1-2, through A-1-M as
the slice names that fall within the slice name range of the
request.
[0043] Having identified the slice names of the stored encoded data
slices associated with the request, the storage unit 36, for a
first slice name 80 of the slice name range, generates a first
portion of a list range response 1 that includes the first slice
name (e.g., A-1-1) in a slice name field 89, an entry of a slice
revision count field 92 corresponding to the first slice name, and,
for each identified revision, the slice revision entry of a slice
revision field 94 and a slice length entry of a slice length field
96. In one example, the slice revision entry includes 00h when
there are no visible slice revisions. The slice length entry
includes a slice length (e.g., number of bytes of the slice) of a
slice revision.
[0044] Having generated the first portion of the list range
response 1, the storage unit 36, for each remaining slice name of
the slice name range, generates further portions of the list range
response 1 that includes a representation of the remaining slice
name in a slice name offset field 81, an entry of another slice
revision count field 92 for the remaining slice name, and, for each
identified revision of the remaining slice name, a slice revision
entry of another slice revision field 94 and a slice length entry
of another slice length field 96.
[0045] The representation of the remaining slice name includes at
least one of an offset from the first slice name based on the
remaining slice name, and a result of applying a deterministic
function to the first slice name and the remaining slice name. For
example, the storage unit 36 generates the representation of the
remaining slice name as 10 when the remaining slice name (e.g.,
A-1-11) is offset by 10 from the first slice name. As such, a size
efficiency is provided as successive slice name offset fields are
smaller in size (e.g., 4-24 bytes) than the slice name field (e.g.,
48 bytes).
[0046] FIG. 10 is a flowchart illustrating an example of
identifying stored encoded data slices. The method begins or
continues at step 100 where a processing module (e.g., of a
dispersed storage (DS) client module) receives a list range request
from a requesting entity, where the request includes a slice name
range. The method continues at step 102 where the processing module
identifies slice names of stored slices that correspond to the
slice name range. For example, the processing module identifies
slice names of stored encoded data slices where the slice names
fall within the slice name range.
[0047] The method continues at step 104 where, for a first slice
name of the slice name range, the processing module generates a
first portion of a list range response that includes the first
slice name and one or more other parameters of one or more
revisions of stored slices associated with the first slice name.
The other parameters include one or more of a slice revision count
of the number of the one or more revisions, a slice revision number
for each slice revision, and a slice length of the stored slice of
each slice revision.
[0048] The method continues at step 106 where, for each remaining
slice name of the slice name range, the processing module generates
another portion of the list range response that includes a
representation of the remaining slice name and one or more other
parameters of one or more revisions of stored slices associated
with the remaining slice name. For example, the processing module
generates the other portion of the list range response to include
an offset from the first slice name as the representation of the
remaining slice name. The method continues at step 108 where the
processing module sends the list range response to the requesting
entity.
[0049] FIGS. 11A-11D are a schematic block diagrams of examples of
list range responses (e.g., a list range response of FIG. 9). The
list range responses identify stored encoded data slices within a
slice name range. For example, a list range response from a storage
unit to a computing device of the DSN includes one or more
representations of a range of slice names that identify the encoded
data slices stored within the storage unit.
[0050] FIG. 11A is an example of a list range response message that
includes a first slice name representation (SNR) 110 and a
subsequent portion(s) representation 112. The first slice name
representation identifies the first slice name. In one example, a
representation is able to identify one or more slice names in
accordance with one or more of a DSN protocol. In one example, the
DSN protocol is based on dispersed storage error encoding
parameters. For example, a data object A is dispersed storage error
encoded in accordance with dispersed storage error encoding
parameters to produce a plurality of sets of encoded data slices
that are stored in a set of storage units of the DSN. In one
example, a first encoded data slice of each set of the plurality of
sets of encoded data slices are grouped into a first group of
encoded data slices (e.g., share a common pillar number (e.g., 1 of
A-1-1 through A-1-M)) and stored in a first storage unit of the set
of storage units in accordance with the DSN protocol.
[0051] 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 (e.g., pillar width, decode threshold,
etc). In this example, a requesting device sends a list request for
a range of encoded data slices A-1-1 through A-1-M. The request can
include a representation structure for the list response.
Alternatively, or in addition to, the representation structure is
based on the DSN protocol (e.g., data segmenting protocol, data
storage protocol, slice naming protocol, etc). For example, a
requesting device determines the DSN protocol is to store the first
pillar number of encoded data slices in the first storage unit. In
this example, the requesting device determines the representation
structure is to exclude (e.g., truncate) the pillar number in a
list response. For example, the first slice name representation is
A-2 for slice name A-1-2 and a first subsequent portion
representation is A-3 for a slice name A-1-3.
[0052] FIG. 11B is an example of a list range response that
includes a first slice name representation 110 and a last slice
name representation 113. In one example, the first and last
representations are of a similar representation structure. For
example, the first slice name representation includes a result
based on a deterministic function applied to the first slice name
and the last slice name representation includes a second result
based on the deterministic function applied to the last slice name.
In a second example, the first and last representations are not of
a similar representation structure. For example, the first slice
name representation is the first slice name and the last slice name
representation is an offset value of the last slice name from the
first slice name.
[0053] FIG. 11C is a schematic block diagram of another example of
a list range response that includes a first slice name
representation (SNR) 110, a first contiguous range SNR 114, another
first SNR and a second contiguous range SNR 116. In one example, a
(e.g., the first) contiguous range SNR 114 includes the first SNR
110 (e.g., based on a DSN protocol). In a second example, the first
contiguous range SNR 114 does not include the first SNR 110.
[0054] As a specific example, a storage device stores encoded data
slices A-1-1 through A-1-M that are associated with a range of
slice names. The storage device receives a list range request for
the range of slice names that are associated with the encoded data
slices A-1-1 through A-1-13. The storage device identifies encoded
data slices A-1-2 through A-1-5 and A-1-7 through A-1-13 as being
stored in memory of the storage device. The storage device
generates the first SNR to include "A-2", the 1.sup.st contiguous
range SNR to include "3" (to represent A-1-3, A-1-4, and A-1-5),
the additional first SNR to include "A-7" and the second contiguous
range SNR to include "6" (to represent A-1-8, A-1-9, A-1-10,
A-1-11, A-1-12 and A-1-13.
[0055] FIG. 11D is a schematic block diagram of another example of
a list range response that includes a first SNR field 110, a
1.sup.st missing SNR field 115, a 2.sup.nd missing SNR field 115
and a last SNR field 113. In an example, the storage unit storing
encoded data slices A-1-1 through A-1-13 receives a list range
request that includes a slice name range and a representation
structure that indicates to respond with a first slice name
representation of the first slice name within the slice name range,
a last slice name representation for the first slice name within
the slice name range, and one or more missing SNRs 115.
[0056] As a specific example, the storage device receives a list
range request for the range of slice names that are associated with
the encoded data slices A-1-1 through A-1-13. The storage device
identifies encoded data slices A-1-2 through A-1-5 and A-1-7
through A-1-13 as being stored in memory of the storage device. The
storage device then generates, according to the representation
structure, the first SNR to include "A-2", the 1.sup.st missing
slice SNR to include A-1-1, the 2.sup.nd missing slice SNR to
include A-1-6 and the last SNR 113 to include A-1-13.
[0057] Note that any of the examples in the preceding figures may
be combined. For example, a list range response may include a first
SNR and a 1.sup.st missing contiguous range SNR. Further note, the
offset may also indicate a difference between a first list range
response and a second list range response. The offset may also be
based on a data object identification, a pillar number, a segment
number and other information within the slice name.
[0058] FIG. 12 is a logic diagram of an example of a method of
listing stored encoded data slices in accordance with the present
invention. The method begins with step 120, where a storage unit
receives a list range request for a plurality of slice names within
a slice name range, wherein the plurality of slice names is
associated with a plurality of encoded data slices stored in the
storage unit. In an example, data is dispersed storage error
encoded into pluralities of sets of encoded data slices and stored
in storage units of the DSN. The dispersed storage error encoding
is in accordance with dispersed data storage parameters and the
pluralities of sets of encoded data slices include the plurality of
encoded data slices stored in the storage unit.
[0059] The method continues with step 122, where the storage unit
identifies slice names of the plurality of slice names within the
slice name range. For example, the storage unit identifies the
slice names associated with encoded data slices stored in the
storage unit within the slice name range.
[0060] The method continues with step 124, where the storage unit
determines a representation structure for a list range response.
The representation structure includes one or more of an offset
representation, a first slice name representation, a last slice
name representation, a deterministic function representation, a
missing encoded data slice representation, a contiguous grouping of
encoded data slices representation, a revision representation
(e.g., all slice lengths or revisions are the same across two or
more slice names, an offset in the revision field, etc.) and any
other information regarding the structure of a list name
response.
[0061] The method continues with step 126, where the storage unit
generates, in accordance with the representation structure, a first
portion of a list range response for a first slice name of the
slice names. The first portion includes a first representation of
the first slice name. As an example, the first representation
includes one of the first slice name, a result based on performing
a deterministic function on the first slice name and a truncated
(e.g., shortened) version of the first slice name. Note the first
portion and the one or more subsequent portions may each further
include a slice revision count field. The slice revision count
field includes one or more slice revision fields and one or more
corresponding slice length fields.
[0062] The method continues with step 128, where the storage unit
generates, in accordance with the representation structure, one or
more subsequent portions of the list range response for remaining
slice names of the slice names. The one or more subsequent portions
includes one or more representations of the remaining slices names.
For example, a representation of the one or more representations
includes one or more of an offset from the first slice name, a
result based on a deterministic function applied to the first slice
name and a remaining slice name of the remaining slice names, a
result based on a number of slice names within a contiguous range
of slice names of the remaining slice names, and a last slice name
of the slice names.
[0063] The method continues with step 130, where the storage unit
sends the list range response to the requesting device. In an
example, list range response further includes one or more of a
request number, a payload length (e.g., a number of bytes after a
header), a first slice name, and a last slice name.
[0064] 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, audio, etc. any of which may generally
be referred to as `data`).
[0065] As may be used herein, the terms "substantially" and
"approximately" provides an industry-accepted tolerance for its
corresponding term and/or relativity between items. Such an
industry-accepted tolerance ranges from less than one percent to
fifty percent and corresponds to, but is not limited to, component
values, integrated circuit process variations, temperature
variations, rise and fall times, and/or thermal noise. Such
relativity between items ranges from a difference of a few percent
to magnitude differences. 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". 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.
[0066] 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.
[0067] As may also be used herein, the terms "processing module",
"processing circuit", "processor", 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,
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, 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, 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, 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,
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.
[0068] 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.
[0069] 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.
[0070] 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 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.
[0071] 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.
[0072] 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.
[0073] 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.
[0074] 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.
[0075] 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.
* * * * *