Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: Techniques are disclosed relating to providing protection groups and rapid determination of expired objects and associated storage resources in a cloud-based backup storage context. In various embodiments, the disclosed techniques include generating, by a computing system, incremental backup data for a backup based on protection group information, including a set of cloud-based key-value data store buckets, filter information, and policy information. Disclosed techniques also include rapid determination of expired objects and associated storage resources. Disclosed techniques may advantageously provide a centralized view across buckets, accounts, and regions and allow users to target specific subsets of their data stores for backup, which may improve performance and reduce backup storage costs, relative to traditional techniques.

Abstract: Techniques are disclosed relating to providing object-level incremental backups and data restoration management techniques in a cloud-based backup storage context. In various embodiments, the disclosed techniques include generating, by a computing system, object-level differentials that maintain differences between successive inventories (e.g., added, deleted, and amended objects) and are used to perform incremental backups. Disclosed techniques also include restoration management methods that leverage parallelization, via chunks of data that may be processed in parallel by cloud worker modules, and protection group mechanisms to restore single buckets, multiple buckets, single objects, multiple objects, objects and buckets that match specific search criteria, etc. Disclosed techniques may advantageously improve performance of data backup and restoration operations, relative to traditional techniques.

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: Selective repair of fragmentation in a synthetic backup, based at least in part on a dynamically-determined repair criteria, is disclosed. In various embodiments, a locality measure is computed with respect to a group of segments comprising a portion of a file. The computed locality measure is compared to an at least partly dynamically determined fragmentation repair criteria, and a repair decision is made based at least in part on the comparison.

Abstract: Fragmentation repair of synthetic backups is disclosed. In various embodiments, a locality measure is computed with respect to a group of segments comprising a portion of a file. The computed locality measure is compared to a repair criteria. A decision whether to repair fragmentation of segments comprising the group is made based at least in part on the comparison.

Abstract: Opportunistic repair of fragmentation in a synthetic backup is disclosed. In various embodiments, data generated to perform processing other than fragmentation repair is received. At least a portion of the received data is used to compute a locality measure with respect to a group of segments comprising a portion of a file. A decision whether to repair fragmentation of segments comprising the group is made based at least in part on the computed locality measure.

Abstract: Exemplary methods for verifying data integrity for garbage collection with limited memory include maintaining a data structure that includes a plurality of entries, storing states of a group of segments compressed therein. In response to receiving a request for transitioning a segment from a first state to a second state, retrieving a first entry value of an entry associated with the first segment, generating a second entry value based on the first entry value, the first state, the second state, and a value obtained from a first lookup table based on the first segment. The methods also include writing back the second entry value to the first entry of the data structure. In one embodiment, in response to determining all entries of the data structure reach a predetermined final state, performing a garbage collection process on the segments stored in the storage system.

Abstract: A garbage collector of a storage system traverses a namespace of a file system of the storage system to verify data integrity of segments. The namespace identifies files that are represented by segments arranged in multiple levels in a hierarchy, where an upper level segment includes one or more references to one or more lower level segments, and at least one segment is referenced by multiple files. Traversing the namespace includes computing and verifying checksums all segments in a level-by-level manner, where checksums of an upper level are verified before any of checksums of a lower level are verified. Upon all checksums of all levels have been verified, a garbage collection process is performed on the segments stored in the storage system.

Abstract: Selective repair of fragmentation in a synthetic backup, based at least in part on a dynamically-determined repair criteria, is disclosed. In various embodiments, a locality measure is computed with respect to a group of segments comprising a portion of a file. The computed locality measure is compared to an at least partly dynamically determined fragmentation repair criteria, and a repair decision is made based at least in part on the comparison.

Abstract: Selective repair of fragmentation in a synthetic backup, based at least in part on a dynamically-determined repair criteria, is disclosed. In various embodiments, a locality measure is computed with respect to a group of segments comprising a portion of a file. The computed locality measure is compared to an at least partly dynamically determined fragmentation repair criteria, and a repair decision is made based at least in part on the comparison.

Abstract: A method for generating automatic design characterization patterns for integrated circuits (IC) is provided. The method includes selecting a routing scheme from a file containing the device description of the routings of the IC. The routing scheme may be of a phase locked loop, clock tree, delay element, or input output block in one embodiment. Resource types for the routing scheme are identified and a path is defined, within constraints, between the resources. Once a path is defined, alternate paths are defined by retracing the path within constraints from an end of the path to the beginning of the path. An alternative path is then built and the alternative path shares a portion of the path previously defined. A computing system providing the functionality of the method is also provided.

Abstract: Programmable circuits have a programmable interconnect structure that connects programmable circuit elements. Tests patterns can be automatically generated for the programmable circuit elements and interconnections on a programmable circuit. A connectivity graph represents programmable interconnections and functions as nodes. Tests routes are generated that connect the nodes in the connectivity graph between control points and observation points on the programmable circuit. The routes are grouped into configuration patterns that can be tested in one test cycle. Test vectors are then applied to the routes to determine if the interconnects and circuit functions are operable. Systems and methods of the present invention automatically create test patterns for a programmable circuit to reduce engineer time. The present invention also reduces test time and resources by increasing the number of interconnections and circuit elements tested in each configuration pattern.