U.S. patent application number 16/124666 was filed with the patent office on 2019-01-03 for de-duplication of data streams.
The applicant listed for this patent is International Business Machines Corporation. Invention is credited to Andrew D. Baptist, Greg R. Dhuse, S. Christopher Gladwin, Gary W. Grube, Wesley B. Leggette, Timothy W. Markison, Manish Motwani, Jason K. Resch, Thomas F. Shirley, JR., Ilya Volvovski.
Application Number | 20190007380 16/124666 |
Document ID | / |
Family ID | 64738467 |
Filed Date | 2019-01-03 |
![](/patent/app/20190007380/US20190007380A1-20190103-D00000.png)
![](/patent/app/20190007380/US20190007380A1-20190103-D00001.png)
![](/patent/app/20190007380/US20190007380A1-20190103-D00002.png)
![](/patent/app/20190007380/US20190007380A1-20190103-D00003.png)
![](/patent/app/20190007380/US20190007380A1-20190103-D00004.png)
![](/patent/app/20190007380/US20190007380A1-20190103-D00005.png)
![](/patent/app/20190007380/US20190007380A1-20190103-D00006.png)
United States Patent
Application |
20190007380 |
Kind Code |
A1 |
Volvovski; Ilya ; et
al. |
January 3, 2019 |
DE-DUPLICATION OF DATA STREAMS
Abstract
A data segment is encrypted to produce an encrypted data
segment, and a data tag associated with the data segment is
generated. The encrypted data segment is encoded to generate a set
of encoded data slices. At least a read-threshold number of encoded
data slices are required to reconstruct the encrypted data segment.
A set of write slice requests, which includes the set of encoded
data slices and the data tag, is transmitted to a DSN memory. A
determination is made, based on the data tag, whether a first
encoded data slice of the set of encoded data slices is a duplicate
of a second encoded data slice already stored within the DSN
memory. If it is a duplicate, rather of storing the first encoded
data slice, a reference to a location of the second encoded data
slice is stored.
Inventors: |
Volvovski; Ilya; (Chicago,
IL) ; Gladwin; S. Christopher; (Chicago, IL) ;
Grube; Gary W.; (Barrington Hills, IL) ; Markison;
Timothy W.; (Mesa, AZ) ; Resch; Jason K.;
(Chicago, IL) ; Shirley, JR.; Thomas F.;
(Wauwatosa, WI) ; Dhuse; Greg R.; (Chicago,
IL) ; Motwani; Manish; (Chicago, IL) ;
Baptist; Andrew D.; (Mt. Pleasant, WI) ; Leggette;
Wesley B.; (Chicago, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation |
Armonk |
NY |
US |
|
|
Family ID: |
64738467 |
Appl. No.: |
16/124666 |
Filed: |
September 7, 2018 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
14172140 |
Feb 4, 2014 |
10075523 |
|
|
16124666 |
|
|
|
|
61807288 |
Apr 1, 2013 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 3/067 20130101;
G06F 11/1076 20130101; H04L 9/0861 20130101; H04L 63/0457 20130101;
G06F 3/0619 20130101; G06F 3/0641 20130101; H04L 9/0894 20130101;
G06F 3/0608 20130101 |
International
Class: |
H04L 29/06 20060101
H04L029/06; H04L 9/08 20060101 H04L009/08; G06F 11/10 20060101
G06F011/10; G06F 3/06 20060101 G06F003/06 |
Claims
1. A method for use in a distributed storage network (DSN), the
method comprising: encrypting a data segment to produce an
encrypted data segment; generating a data tag associated with the
data segment; encoding the encrypted data segment to generate a set
of encoded data slices including a plurality of encoded data
slices, wherein at least a read-threshold number of the plurality
of encoded data slices included in the set of encoded data slices
is required to reconstruct the encrypted data segment; transmitting
a set of write slice requests to a DSN memory, the set of write
slice requests including the set of encoded data slices, and the
data tag; determining, based on the data tag, whether a first
encoded data slice of the set of encoded data slices is a duplicate
of a second encoded data slice already stored within the DSN
memory; and in response to determining that the first encoded data
slice is a duplicate of the second encoded data slice, storing a
reference to a location where the second encoded data slice is
stored, instead of storing the first encoded data slice.
2. The method of claim 1, further comprising: generating a key
masking the key to generate a masked key; and including the masked
key in the encrypted data segment prior to generating the set of
encoded data slices.
3. The method of claim 1, further comprising: generating a key
obfuscating the key to generate an obfuscated key; and storing the
obfuscated key as metadata associated with the data segment.
4. The method of claim 1, further comprising: generating the data
tag by applying a deterministic function to the data segment prior
to encrypting the data segment.
5. The method of claim 1, further comprising: generating the data
tag by applying a deterministic function to the encrypted data
segment.
6. The method of claim 1, further comprising: in response to
determining that the first encoded data slice is not duplicated
within the DSN memory: storing the first encoded data slice at a
location associated with a distributed storage (DS) unit included
in the DSN memory; and outputting, to other DS units included in
the DSN memory, information associating a storage location of the
first encoded data slice with the data tag.
7. The method of claim 1, further comprising: extracting the data
tag from a write slice request to generate an extracted data tag;
and comparing the extracted data tag to a data tag list including a
list of data tags associated with encoded data slices already
stored in the DSN memory.
8. A distributed storage network (DSN) comprising: a distributed
storage (DS) processing module including a processor and associated
memory, the DS processing module configured to: encrypt a data
segment to produce an encrypted data segment; generate a data tag
associated with the data segment; encode the encrypted data segment
to generate a set of encoded data slices including a plurality of
encoded data slices, wherein at least a read-threshold number of
the plurality of encoded data slices included in the set of encoded
data slices is required to reconstruct the encrypted data segment;
transmit a set of write slice requests to a DSN memory, the set of
write slice requests including the set of encoded data slices, and
the data tag; a DSN memory including a processor and associated
memory, and further including a plurality of DS units, the DSN
memory configured to: determine, based on the data tag, whether a
first encoded data slice of the set of encoded data slices is a
duplicate of a second encoded data slice already stored within the
DSN memory; and store error encoded data slices on behalf of the
DSN, the DSN memory configured to, in response to determining that
the first encoded data slice is a duplicate of the second encoded
data slice, store a reference to a location where the second
encoded data slice is stored, instead of storing the first encoded
data slice.
9. The distributed storage network (DSN) of claim 8, wherein the DS
processing module is further configured to: generate a key mask the
key to generate a masked key; and include the masked key in the
encrypted data segment prior to generating the set of encoded data
slices.
10. The distributed storage network (DSN) of claim 8, wherein the
DS processing module is further configured to: generate a key
obfuscate the key to generate an obfuscated key; and store the
obfuscated key as metadata associated with the data segment.
11. The distributed storage network (DSN) of claim 8, wherein the
DS processing module is further configured to: generate the data
tag by applying a deterministic function to the data segment prior
to encrypting the data segment.
12. The distributed storage network (DSN) of claim 8, wherein the
DS processing module is further configured to: generate the data
tag by applying a deterministic function to the encrypted data
segment.
13. The distributed storage network (DSN) of claim 8, wherein the
DSN memory is further configured to: in response to determining
that the first encoded data slice is not duplicated within the DSN
memory: store the first encoded data slice at a location associated
within a distributed storage (DS) unit; and output, to other DS
units included in the DSN memory, information associating a storage
location of the first encoded data slice with the data tag.
14. The distributed storage network (DSN) of claim 8, wherein the
DSN memory is further configured to: extract the data tag from a
write slice request to generate an extracted data tag; and compare
the extracted data tag to a data tag list including a list of data
tags associated with encoded data slices already stored in the DSN
memory.
15. A distributed storage network (DSN) memory comprising: a
processor and associated memory; a plurality of distributed storage
(DS) units coupled to the processor and associated memory; the
processor and associated memory configured to: receive a set of
write slice requests from DS processing module, the set of write
slice requests including a set of encoded data slices, and a data
tag, wherein the set of encoded data slices includes a plurality of
encoded data slices generated from an encrypted data segment, and
wherein at least a read-threshold number of encoded data slices
included in the set of encoded data slices is required to
reconstruct the encrypted data segment; determine, based on the
data tag, whether a first encoded data slice of the set of encoded
data slices is a duplicate of a second encoded data slice already
stored by a DS unit included in the DSN memory; and in response to
determining that the first encoded data slice is a duplicate of the
second encoded data slice, store a reference to a location where
the second encoded data slice is stored, instead of storing the
first encoded data slice.
16. The distributed storage network (DSN) memory of claim 15,
wherein the set of write slice requests includes metadata, the
metadata including an obfuscated key.
17. The distributed storage network (DSN) memory of claim 15,
further configured to: extract the data tag from a write slice
request to generate an extracted data tag; and compare the
extracted data tag to a data tag list including a list of data tags
associated with encoded data slices already stored in the DSN
memory.
18. The distributed storage network (DSN) memory of claim 15,
further configured to: in response to determining that the first
encoded data slice is not duplicated within the DSN memory: store
the first encoded data slice at a location associated within a
distributed storage (DS) unit; and output, to other DS units
included in the DSN memory, information associating a storage
location of the first encoded data slice with the data tag.
19. The distributed storage network (DSN) memory of claim 18,
further configured to: store metadata associated with the first
encoded data slice in one of the plurality of distributed storage
(DS) units included in the DSN memory.
20. The distributed storage network (DSN) memory of claim 15,
wherein: the reference to a location where the second encoded data
slice is stored includes a reference to an alternate DS unit.
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. Utility application
Ser. No. 14/172,140, entitled "EFFICIENT STORAGE OF DATA IN A
DISPERSED STORAGE NETWORK", filed Feb. 4, 2014, scheduled to issue
as U.S. Pat. No. 10,075,523 on Sep. 11, 2018, which claims priority
pursuant to 35 U.S.C. .sctn. 119(e) to U.S. Provisional Application
No. 61/807,288, entitled "DE-DUPLICATING DATA STORED IN A DISPERSED
STORAGE NETWORK", filed Apr. 1, 2013, both 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.
BACKGROUND
[0002] This invention relates generally to computer networks and
more particularly to de-duplicating dispersing error encoded
data.
[0003] 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.
[0004] 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.
[0005] 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.
[0006] Conventional systems sometimes de-duplicate data by, for
example, removing extra copies of stored data files. But known
de-duplication techniques may not be able to achieve maximum
effectiveness when used in conjunction with various distributed
storage techniques.
SUMMARY
[0007] According to an embodiment of the present invention, A
method for use in a distributed storage network (DSN) includes
encrypting a data segment to produce an encrypted data segment,
generating a data tag associated with the data segment, and
encoding the encrypted data segment to generate a set of encoded
data slices including multiple encoded data slices. At least a
read-threshold number of the plurality of encoded data slices
included in the set of encoded data slices can be required to
reconstruct the encrypted data segment.
[0008] In some embodiments, the data tag is generated by applying a
deterministic function to the data segment prior to encrypting the
data segment, while other embodiments apply the deterministic
function to the already-encrypted data segment.
[0009] The method can include transmitting a set of write slice
requests to a DSN memory, the set of write slice requests including
the set of encoded data slices, and the data tag, and determining,
based on the data tag, whether a first encoded data slice of the
set of encoded data slices is a duplicate of a second encoded data
slice already stored within the DSN memory. In response to
determining that the first encoded data slice is a duplicate of the
second encoded data slice, instead of storing the first encoded
data slice, the method stores a reference to a location where the
second encoded data slice has been previously stored. Later, when a
data segment is read, the data can be obtained from the original
storage location by using the stored reference.
[0010] In some embodiments, a key is generated, masked, and
included in the encrypted data segment prior to encoding the
encrypted data segment to generate encoded data slices. In other
embodiments, a key is generated, obfuscated, and inserted into
metadata associated data segment.
[0011] In some embodiments, when an encoded data slice is stored in
a distributed storage (DS) unit of a DSN memory, information
associating a storage location of the encoded data slice with the
data tag is output to other DS units included in the DSN memory. In
some implementations, the a DSN memory can extract the data tag
from a write slice request to generate an extracted data tag, and
the extracted data tag is compared against a data tag list
including a list of data tags associated with encoded data slices
already stored in the DSN memory.
[0012] Various implementations include a system having a DSN
memory, and associated DS units and a DS processing unit.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] FIG. 1 is a schematic block diagram of an embodiment of a
dispersed or distributed storage network (DSN) in accordance with
the present invention;
[0014] FIG. 2 is a schematic block diagram of an embodiment of a
computing core in accordance with the present invention;
[0015] FIG. 3 is a schematic block diagram of an example of
dispersed storage error encoding of data in accordance with the
present invention;
[0016] FIG. 4 is a schematic block diagram of a generic example of
an error encoding function in accordance with the present
invention;
[0017] FIG. 5 is a schematic block diagram of a specific example of
an error encoding function in accordance with the present
invention;
[0018] 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;
[0019] FIG. 7 is a schematic block diagram of an example of
dispersed storage error decoding of data in accordance with the
present invention;
[0020] FIG. 8 is a schematic block diagram of a generic example of
an error decoding function in accordance with the present
invention;
[0021] FIG. 9 is a schematic block diagram of an embodiment of a
dispersed storage system in accordance with the present invention;
and
[0022] FIG. 10 is a flowchart illustrating an example of storing
data in accordance with the present invention.
DETAILED DESCRIPTION
[0023] 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).
[0024] 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.
[0025] 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.
[0026] 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 and 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.
[0027] 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 (e.g., 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).
[0028] 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 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.
[0029] The 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.
[0030] The managing unit 18 creates billing information for a
particular user, a user group, a vault access, public vault access,
etc. For instance, the 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 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.
[0031] 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.
[0032] 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.
[0033] 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.
[0034] 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.
[0035] 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.).
[0036] 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.
[0037] 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.
[0038] 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.
[0039] 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.
[0040] 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.
[0041] 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.
[0042] 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.
[0043] Referring next to FIGS. 9 and 10, various embodiments for
de-duplicating data in a distributed storage system will be
discussed. In some embodiments, a requester submits a stream of
data to a distributed storage (DS) processing unit. The DS
processing unit segments the stream into segments of a certain
size, which may be determined as a preferred segment size for a
group of processing units storing data to the same de-dupe system.
If security is required, then convergent all or nothing
transformation (AONT) or convergent encryption can be applied to
the individual segments prior to slicing. This enables
deduplication between data streams containing at least one
contiguous segment worth of identical data. De-duplication may be
performed either as an intermediate step prior to storage on ds
units, or the ds units themselves may perform the de-duplication by
checking whether or not data having the same "data tag" exists for
the segment (or for the slices). When a DS unit receives a slice
for which the data tag is already known, instead of storing the
slice it stores a reference to where the unique copy of the slice
exists within the de-duped system. For security purposes, knowledge
of the data tag may be sufficient to access the given data. This
enables one ds unit to access the de-duped data on another ds unit,
even if the ds unit would not otherwise have access.
[0044] FIG. 9 is a schematic block diagram of an embodiment of a
dispersed storage system that includes a plurality of user devices
14, such as computing device 12 of FIG. 1, a plurality of dispersed
storage (DS) processing modules 350, and a dispersed storage
network (DSN) memory 352. The DSN memory 352 includes a plurality
of DS units 354. The DS units 354 may be organized into one or more
sets of DS units 354. Each DS unit 354 of the one or more sets of
DS units may be implemented utilizing one or more of a storage
node, a dispersed storage unit, the storage unit 36 of FIG. 1, a
storage server, a storage module, a memory device, a memory, a user
device, a DST processing unit, such as computing device 16 of FIG.
1, and a DST processing module. Each DS processing module 350 of
the plurality of DS processing modules may be implemented by at
least one of a server, a computer, a DS unit, a user device, a
processing module, a DS processing unit, a DST processing module,
and a DST processing unit, such as computing device 16 of FIG.
1.
[0045] The system functions to store data in the DSN memory 352 in
accordance with a data de-duplication approach. In an example of
operation of the data de-duplication approach, a first user device
14 issues a first store data request 356 to a first DS processing
module 350 to store data in the DSN memory 352, where the first
store data request 356 includes the data and a data identifier (ID)
of one or more data IDs associated with the data. As an example of
utilization of another data ID, a second user device 14 sends a
second store data request 356 to a second DS processing module 350,
where the second store data request 356 includes other data (e.g.,
that is identical to the data from the first user device 14) and
another data ID associated with the other data.
[0046] Having received the first store data request 356 from the
first user device 14, the first DS processing module 350 partitions
the data to produce a plurality of data segments in accordance with
a data segmentation approach. For a data segment of the plurality
of data segments, the first DS processing module 350 encrypts the
data segment to produce an encrypted data segment utilizing at
least one of convergent encryption or convergent all or nothing
transformation (AONT) encryption. Alternatively, or in addition to,
the first DS processing module 350 selects one of the convergent
encryption and the convergent AONT encryption based on one or more
of a security requirement, a retrieval requirement, a performance
requirement, a lookup, a query, receiving an indicator, and a
predetermination. When utilizing convergent encryption, the first
DS processing module 350 applies a deterministic function to the
data segment to generate a deterministic key and stores metadata
associated with the data segment that includes the deterministic
key. The storing may include encrypting the deterministic key using
a public key of the first user device 14. The storing may further
include storing the metadata in at least one of a local memory of
the first DS processing module 350, a local memory of the first
user device 14, and in the DSN memory 352 as a set of encoded
metadata slices.
[0047] When storing the metadata in the DSN memory 352, the first
DS processing module 350 encodes the metadata using a dispersed
storage error coding function to produce the set of encoded
metadata slices, generates a set of slice names associated with
metadata of the data ID, generates a set of write slice requests
that includes the set of encoded metadata slices and the set of
slice names, and outputs the set of write slice requests to the DSN
memory 352. When utilizing convergent AONT encryption, the first DS
processing module 350 generates a random key, performs a
deterministic function on the encrypted data to produce a digest,
masks the random key using the digest to produce a masked key, and
appends the masked key to the encrypted data to produce a secure
package as an updated encrypted data segment.
[0048] The first DS processing module 350 generates a data tag
based on the data segment. The generating includes at least one of
applying a deterministic function to the data segment and applying
the deterministic function to the encrypted data segment. The
deterministic function may include at least one of a hashing
function, a hash-based message authentication code (HMAC) function,
a mask generating function (MGF), and a sponge function. The first
DS processing module 350 encodes the encrypted data segment using
the dispersed storage error coding function to produce a set of
encoded data slices. The first DS processing module 350 generates a
set of slice names for the set of encoded data slices to correspond
to one or more of the data ID, the data tag, a user device ID, and
a vault ID associated with the user device. For example, the first
DS processing module 350 generates a source name based on a vault
ID associated with the user device and generates the set of slice
names to include the source name in accordance with dispersed
storage error coding parameters. The first DS processing module 350
generates a set of write slice requests 358 that includes the set
of encoded data slices, the data tag, and the set of slice names.
The first DS processing module 350 outputs the set of write slice
requests 358 to a set of DS units 354 of the DSN memory 352.
[0049] For each DS unit 354 of the set of DS units 354, the DS unit
354 receives a corresponding write slice request 358 of the set of
write slice requests and determines whether a received encoded data
slice is duplicated within the DSN memory 352 based on the data tag
of the write slice request 358. The determining may be based on one
or more of comparing the data tag to a data tag list associated
with the DSN memory 352, initiating a query, generating another
data tag for an encoded data slice that was not previously
associated with a data tag, and receiving a query result.
[0050] When the DS unit 354 determines that the encoded data slice
is not duplicated within the DSN memory 352, the DS unit 354 stores
the encoded data slice locally, stores metadata locally (e.g.,
including a local storage location associated with storage of the
encoded data slice), and updates the data tag list associated with
the DSN memory 352 to include a location indicator for the encoded
data slice corresponding to the data tag and slice name associated
with the encoded data slice. When the DS unit 354 determines that
the encoded data slice is duplicated within the DSN memory 352, the
DS unit 354 stores the metadata locally, where the metadata
includes another storage location associated with storage of
another encoded data slice that is a duplicate of the received
encoded data slice.
[0051] In an example of retrieval of the data, a retrieving user
device 14 must have previously stored the data such that metadata
is stored associated with a data ID used by the retrieving user
device and recovery of the deterministic key requires decrypting
the deterministic key recovered from the metadata using a private
key associated with the user device. In an example of operation
when the retrieving user device has not previously stored the data,
the data is only recoverable when the data was stored utilizing the
convergent AONT encryption approach since the random key is
recovered by de-appending a recovered secure package
[0052] FIG. 10 is a flowchart illustrating an example of storing
data. The method begins at step 360 where a processing module
(e.g., of a dispersed storage processing module) generates a key.
The generating includes at least one of performing a deterministic
function on data for storage to produce the key and generating a
random key when utilizing an all or nothing transformation (AONT)
approach for storing the key in a subsequent step. The method
continues at step 362 where the processing module encrypts a data
segment of the data using the key to produce an encrypted data
segment. The method continues at step 364 where the processing
module generates a data tag based on the data segment. The
generating includes performing a deterministic function on one or
more of the key and the encrypted data segment. The method
continues at step 366 where the processing module encodes the
encrypted data segment using a dispersed storage error coding
function to produce a set of encoded data slices.
[0053] The encoding may further include obfuscating the key to
produce at least one of an encrypted key and a masked key. When
producing the encrypted key, the processing module encrypts the key
with a public key associated with a requesting entity to produce
the encrypted key. When producing the master key, the processing
module performs a deterministic function on the encrypted data
segment to produce a digest, masks the key using the digest (e.g.,
performing an exclusive OR function on the key and the digest) to
produce the masked key which is appended to the encrypted data
segment. The method continues at step 368 where the processing
module generates a set of slice names. The generating may be based
on one or more of a data identifier of the data, a vault
identifier, a user device identifier, and the data tag.
[0054] The method continues at step 370 where the processing module
issues a set of write slice requests to a dispersed storage network
(DSN) memory that includes the data tag, the set of encoded data
slices, and a set of slice names. When not utilizing the AONT
approach, the processing module stores the encrypted key in the DSN
memory as metadata associated with the data (e.g., issues a set of
write slice requests to the DSN memory that includes a set of
encrypted key slices generated by encoding the encrypted key using
the dispersed storage error coding function).
[0055] The method continues at step 372 where a dispersed storage
(DS) unit of the DSN memory receives a write slice request of the
set of write slice requests. The method continues at step 374 where
the DS unit extracts the data tag from the write slice request as
an extracted data tag. The method continues at step 376 where the
DS unit determines whether the extracted data tag is associated
with storage of a previously stored encoded data slice. The
determining includes one or more of comparing the extracted data
tag to a data tag list, initiating a query, and accessing a
hierarchical dispersed index that includes a plurality of data tags
associated with a plurality of data IDs and DSN storage location
addresses. The method branches to step 382 when the extracted data
tag is associated with storage of the previously stored encoded
data slice. The method continues to step 378 when the extracted
data tag is not associated with storage of the previously stored
encoded data slice.
[0056] The method continues at step 378 where the DS unit stores an
extracted encoded data slice locally when the extracted data tag is
not associated with storage of the previously stored encoded data
slice. The storing may further include storing metadata associated
with the extracted encoded data slice when the metadata is received
with the write slice request. The method continues at step 380
where the DS unit associates a local storage location of the
extracted encoded data slice and an extracted data tag. The
associating includes storing association information locally and
outputting the association information to other DS units of the DSN
memory. The method continues at step 382 where the DS unit
associates a storage location of the previously stored encoded data
slice and the extracted data tag when the extracted data tag is
associated with storage of the previously stored encoded data
slice. The associating includes storing association information
locally.
[0057] 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`).
[0058] 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.
[0059] 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".
[0060] 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.
[0061] 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.
[0062] 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".
[0063] 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.
[0064] 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.
[0065] 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.
[0066] 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.
[0067] 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.
[0068] 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.
[0069] 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.
[0070] 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.
[0071] 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.
* * * * *