The present invention relates generally to systems, apparatus, and methods for distributed data storage, and more particularly to systems, apparatus, and methods for distributed data storage using an information dispersal algorithm so that no one location will store an entire copy of stored data, and more particularly still to systems, apparatus, and methods for using a fixed number of slice servers to implement a plurality of dispersed data storage networks.
Storing data in digital form is a well-known problem associated with all computer systems, and numerous solutions to this problem are known in the art. The simplest solution involves merely storing digital data in a single location, such as a punch film, hard drive, or FLASH memory device. However, storage of data in a single location is inherently unreliable. The device storing the data can malfunction or be destroyed through natural disasters, such as a flood, or through a malicious act, such as arson. In addition, digital data is generally stored in a usable file, such as a document that can be opened with the appropriate word processing software, or a financial ledger that can be opened with the appropriate spreadsheet software. Storing an entire usable file in a single location is also inherently insecure as a malicious hacker only need compromise that one location to obtain access to the usable file.
To address reliability concerns, digital data is often “backed-up,” i.e., an additional copy of the digital data is made and maintained in a separate physical location. For example, a backup tape of all network drives may be made by a small office and maintained at the home of a trusted employee. When a backup of digital data exists, the destruction of either the original device holding the digital data or the backup will not compromise the digital data. However, the existence of the backup exacerbates the security problem, as a malicious hacker can choose between two locations from which to obtain the digital data. Further, the site where the backup is stored may be far less secure than the original location of the digital data, such as in the case when an employee stores the tape in her home.
Another method used to address reliability and performance concerns is the use of a Redundant Array of Independent Drives (“RAID”). RAID refers to a collection of data storage schemes that divide and replicate data among multiple storage units. Different configurations of RAID provide increased performance, improved reliability, or both increased performance and improved reliability. In certain configurations of RAID, when digital data is stored, it is split into multiple units, referred to as “stripes,” each of which is stored on a separate drive. Data striping is performed in an algorithmically certain way so that the data can be reconstructed. While certain RAID configurations can improve reliability, RAID does nothing to address security concerns associated with digital data storage.
One method that prior art solutions have addressed security concerns is through the use of encryption. Encrypted data is mathematically coded so that only users with access to a certain key can decrypt and use the data. Common forms of encryption include DES, AES, RSA, and others. While modern encryption methods are difficult to break, numerous instances of successful attacks are known, some of which have resulted in valuable data being compromised.
In 1979, two researchers independently developed a method for splitting data among multiple recipients called “secret sharing.” One of the characteristics of secret sharing is that a piece of data may be split among n recipients, but cannot be known unless at least t recipients share their data, where n≧t. For example, a trivial form of secret sharing can be implemented by assigning a single random byte to every recipient but one, who would receive the actual data byte after it had been bitwise exclusive orred with the random bytes. In other words, for a group of four recipients, three of the recipients would be given random bytes, and the fourth would be given a byte calculated by the following formula:
s′=s⊕ra⊕rb⊕rc,
where s is the original source data, ra, rb, and rc are random bytes given to three of the four recipients, and s′ is the encoded byte given to the fourth recipient. The original byte s can be recovered by bitwise exclusive-orring all four bytes together.
The problem of reconstructing data stored on a digital medium that is subject to damage has also been addressed in the prior art. In particular, Reed-Solomon and Cauchy Reed-Solomon coding are two well-known methods of dividing encoded information into multiple slices so that the original information can be reassembled even if all of the slices are not available. Reed-Solomon coding, Cauchy Reed-Solomon coding, and other data coding techniques are described in “Erasure Codes for Storage Applications,” by Dr. James S. Plank, which is hereby incorporated by reference.
Schemes for implementing dispersed data storage networks (“DDSN”), which are also known as dispersed data storage grids, are also known in the art. In particular, U.S. Pat. No. 5,485,474, issued to Michael O. Rabin, describes a system for splitting a segment of digital information into n data slices, which are stored in separate devices. When the data segment must be retrieved, only m of the original data slices are required to reconstruct the data segment, where n>m.
Prior art DDSN systems are only viable for extremely specialized applications, as implementing an effective DDSN requires that a user setup a network of slice servers in multiple physically disparate locations. Existing directory service software will not effectively manage access to a DDSN, particularly as a DDSN does not have physical resources in the sense of a disk drive or directory, but rather is a type of virtual drive, where information is spread across numerous slice servers. Therefore, software for managing access to a DDSN would make DDSN technology accessible to a wider variety of applications.
In addition, the management and administration of a DDSN presents other problems that are not associated with prior art systems. For example, different users of a DDSN may want to store their data in different ways, i.e., one user may want all of their data compressed to save on storage space, while another user may not want to compress their data to improve retrieval speed. Further, a network of slice servers can be used to implement numerous DDSNs, each having different characteristics, and using a subset or all of the available slice servers to store data.
Although the characteristic features of this invention will be particularly pointed out in the claims, the invention itself, and the manner in which it may be made and used, may be better understood by referring to the following description taken in connection with the accompanying drawings forming a part hereof, wherein like reference numerals refer to like parts throughout the several views and in which:
Turning to the Figures and to
As explained herein, the disclosed invention allows a network of slice servers to implement numerous dispersed data storage networks. In accordance with the disclosed invention, a subset of the available slice servers 150-162 is associated with a user account to form a dispersed data storage network. This information is stored in an accessible location, such as a grid access computer 120, 122, on each client computer 102, 104, 106, or elsewhere. This software construct, which is referred to herein as a “vault,” allows for numerous DDSNs to be implemented from a network of slice servers. Each vault makes use of some number of slice servers, and a particular slice server may be associated with any number of vaults. There is no fixed relation between slice servers comprising a vault, except by the vault construct itself. By example, a first vault may be comprised of 16 slice servers. A second vault may utilize 4 slice servers in common with the first vault, and an additional 8 that are not used by the first vault.
In addition to storing information about what slice servers make up a particular DDSN, a vault will also store other information pertinent to the operation of a DDSN. This information includes what information dispersal algorithm (“IDA”) is used on the DDSN, as well as the information required to operate the particular IDA, such as the number of slices that each data segment is divided into as well, which is also referred to as the quantity n, and the minimum number of data slices required to reconstruct a stored data segment, which is also referred to as the quantity m.
The vault also conglomerates other information that is relevant to the operation of a DDSN. The total storage that is available in a particular vault is stored, as well as the amount of storage that is presently occupied by data segments. In a fee-for-service system, this will prevent a particular user from using more storage than was paid for. In addition, a particular vault may require that data be encrypted, either before it is sliced, after it is sliced, or both before and after it is sliced. Accordingly, the vault structure can contain a field indicating that data segments and/or data slices are encrypted, as well as the particular algorithm that is used for encryption.
For certain applications, data stored on a DDSN may be compressed to increase the total amount of storage available. However, the use of compression can increase the time required to write and retrieve data. Accordingly, the vault can contain a field indicating if compression is to be used, and what type of compression should be used. In addition, while almost every DDSN makes use of integrity checks, certain applications may be better served by different types of integrity checks. For this purpose, the vault may contain a field allowing a user to specify a specific type of integrity check to be used for stored data segments as well as for stored data slices.
In addition to storing information about the particular DDSN associated with a vault, a vault may also include an access control list specifying which accounts are allowed to access the vault, and what permissions are associated with that account. For example, one user may have full access to a vault, while another user may only be allowed to read data segments from the vault, and not write data segments to, or modify data segments stored on the vault.
The foregoing description of the invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or to limit the invention to the precise form disclosed. The description was selected to best explain the principles of the invention and practical application of these principles to enable others skilled in the art to best utilize the invention in various embodiments and various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention not be limited by the specification, but be defined by the claims set forth below.
Number | Name | Date | Kind |
---|---|---|---|
4092732 | Ouchi | May 1978 | A |
5485474 | Rabin | Jan 1996 | A |
5809285 | Hilland | Sep 1998 | A |
5890156 | Rekieta et al. | Mar 1999 | A |
5987622 | Lo Verso et al. | Nov 1999 | A |
5991414 | Garay et al. | Nov 1999 | A |
6012159 | Fischer et al. | Jan 2000 | A |
6058454 | Gerlach et al. | May 2000 | A |
6128277 | Bruck et al. | Oct 2000 | A |
6192472 | Garay et al. | Feb 2001 | B1 |
6256688 | Suetaka et al. | Jul 2001 | B1 |
6272658 | Steele et al. | Aug 2001 | B1 |
6366995 | Vilkov et al. | Apr 2002 | B1 |
6374336 | Peters et al. | Apr 2002 | B1 |
6879596 | Dooply | Apr 2002 | B1 |
6415373 | Peters et al. | Jul 2002 | B1 |
6418539 | Walker | Jul 2002 | B1 |
6449688 | Peters et al. | Sep 2002 | B1 |
6785768 | Peters et al. | Oct 2002 | B2 |
6760808 | Peters et al. | Dec 2002 | B2 |
7024609 | Wolfgang et al. | Jan 2003 | B2 |
6567948 | Steele et al. | May 2003 | B2 |
6571282 | Bowman-Amuah | May 2003 | B1 |
6609223 | Wolfgang | Aug 2003 | B1 |
6718361 | Basani et al. | Apr 2004 | B1 |
7103824 | Halford | Jun 2004 | B2 |
6826711 | Moulton et al. | Nov 2004 | B2 |
7003688 | Pittelkow et al. | Feb 2006 | B1 |
7024451 | Jorgenson | Apr 2006 | B2 |
7103915 | Redlich et al. | Sep 2006 | B2 |
7111115 | Peters et al. | Sep 2006 | B2 |
7140044 | Redlich et al. | Nov 2006 | B2 |
7146644 | Redlich et al. | Dec 2006 | B2 |
7171493 | Shu et al. | Jan 2007 | B2 |
7240236 | Cutts et al. | Jul 2007 | B2 |
7546427 | Gladwin et al. | Jun 2009 | B2 |
20020166079 | Ulrich et al. | Nov 2002 | A1 |
20040024963 | Talagala et al. | Feb 2004 | A1 |
20050114594 | Corbett et al. | May 2005 | A1 |
20050125593 | Karpoff et al. | Jun 2005 | A1 |
20050144382 | Schmisseur | Jun 2005 | A1 |
20060047907 | Shiga et al. | Mar 2006 | A1 |
20060224603 | Correll | Oct 2006 | A1 |
20070079081 | Gladwin et al. | Apr 2007 | A1 |
20070079082 | Gladwin et al. | Apr 2007 | A1 |
20070079083 | Gladwin et al. | Apr 2007 | A1 |
20070174192 | Gladwin et al. | Jul 2007 | A1 |
Number | Date | Country | |
---|---|---|---|
20090094251 A1 | Apr 2009 | US |