Abstract: A method is provided for efficiently recovering information in a distributed storage system where a list of values that should be stored on a storage device is maintained. A first convergence round is scheduled to be performed on the list of values to bring each value to an At Maximum Redundancy (AMR) state. A second convergence round is scheduled to be performed on the list by selecting a wait time interval from a predefined range of wait time intervals between starts of convergence rounds.

Abstract: A server receives information that identifies which chunks are stored in local caches at client computers and receives a request to evict a chunk from a local cache of a first one of the client computers. The server determines whether the chunk stored at the local cache of the first one of the client computers is globally oldest among the chunks stored in the local caches at the client computers, and authorizes the first one of the client computers to evict the chunk when the chunk is the globally oldest among the chunks stored in the local caches at the client computers.

Abstract: Erasure-encoded data is stored across a plurality of storage devices in a data storage system. The erasure-encoded data includes k data elements to store on k data storage devices and m parity elements to store on m parity storage devices, wherein for a given minimum Hamming distance d of the data storage system and m?(d?1), data elements are assigned only to corresponding unique combinations of parity elements of size (d?1).

Abstract: A method for measuring consistability of a distributed storage system is disclosed. The method includes determining at least one consistency level that the distributed storage system can provide. A plurality of failure classes can be determined for the distributed storage system. A probability of the distributed storage system to be in each of the plurality of failure classes can be measured. Each failure class can be mapped to the at least one consistency level. The probability of each failure class for each consistency level can be summed to determine an expected portion of time that the distributed storage system provides each consistency level.

Abstract: A method of recovering a value in a data storage system includes maintaining a list of entries corresponding to values that have been inserted into the data storage system, determining whether the values are at an At Maximum Redundancy (AMR) state, and if not, the converging the values to the AMR state.

Abstract: A system comprises a processor and storage containing software executable by the processor. The storage also contains a trace log that contains information pertaining to read and write operations and, for each read and write operation, the information is indicative of a start time, a completion time, and a value targeted by the read or write operation, Based on the trace log, the software causes the processor to construct a directed graph comprising nodes as well as edges interconnecting at least some of the nodes, each node representing a read or write operation and determine whether the constructed directed graph has a cycle. At least one edge is at least one of a data edge representing a data precedence between operations and a time edge representing a time precedence between operations, and at least one edge is a hybrid edge representing both time and data precedence between operations.

Abstract: Systems and methods of enhanced backup job scheduling are disclosed. An example method may include determining a number of jobs (n) in a backup set, determining a number of tape drives (m) in the backup device, and determining a number of concurrent disk agents (maxDA) configured for each tape drive. The method may also include defining a scheduling problem based on n, m, and maxDA. The method may also include solving the scheduling problem using an integer programming (IP) formulation to derive a bin-packing schedule that minimizes makespan (S) for the backup set.

Abstract: Embodiments include methods, apparatus, and systems for managing jobs in a shared file system. One embodiment includes a method that intercepts file accesses within a job on a client to a storage device in a shared file system, detects when a file associated with the job changes, and sends the client a message of the change.

Abstract: A server receives information that identifies which chunks are stored in local caches at client computers and receives a request to evict a chunk from a local cache of a first one of the client computers. The server determines whether the chunk stored at the local cache of the first one of the client computers is globally oldest among the chunks stored in the local caches at the client computers, and authorizes the first one of the client computers to evict the chunk when the chunk is the globally oldest among the chunks stored in the local caches at the client computers.

Abstract: A method is provided for efficiently recovering information in a distributed storage system where a list of values that should be stored on a storage device is maintained. A first convergence round is scheduled to be performed on the list of values to bring each value to an At Maximum Redundancy (AMR) state. A second convergence round is scheduled to be performed on the list by selecting a wait time interval from a predefined range of wait time intervals between starts of convergence rounds.

Abstract: A method of caching data in a global cache distributed amongst a plurality of computing devices, comprising providing a global cache for caching data accessible to interconnected client devices, where each client contributes a portion of its main memory to the global cache. Each client also maintains an ordering of data that it has in its cache portion. When a remote reference for a cached datum is made, both the supplying client and the requesting client adjust their orderings to reflect the fact that the number of copies of the requested datum now likely exist in the global cache.

Abstract: Erasure-encoded data is stored across a plurality of storage devices in a data storage system. The erasure-encoded data includes k data elements to store on k data storage devices and m parity elements to store on m parity storage devices, wherein for a given minimum Hamming distance d of the data storage system and m?(d?1), data elements are assigned only to corresponding unique combinations of parity elements of size (d?1).

Abstract: A method is provided for scrubbing information stored in a data storage system where the information is stored as a plurality of encoded fragments across multiple storage devices. The method includes maintaining on a first storage device a list of metadata entries corresponding to values that are stored in the data storage system at an At Maximum Redundancy (AMR) state, verifying that encoded fragments associated with each of the metadata entries are stored on a second storage, verifying that a corresponding metadata entry is stored on the first storage device for each encoded fragment that is stored on the second storage device, and scheduling for recovery any missing encoded fragments and/or any missing metadata entry.

Abstract: A method of caching data in a global cache distributed amongst a plurality of computing devices, comprising providing a global cache for caching data accessible to interconnected client devices, where each client contributes a portion of its main memory to the global cache. Each client also maintains an ordering of data that it has in its cache portion. When a remote reference for a cached datum is made, both the supplying client and the requesting client adjust their orderings to reflect the fact that the number of copies of the requested datum now likely exist in the global cache.

Abstract: A method for measuring consistability of a distributed storage system is disclosed. The method includes determining at least one consistency level that the distributed storage system can provide. A plurality of failure classes can be determined for the distributed storage system. A probability of the distributed storage system to be in each of the plurality of failure classes can be measured. Each failure class can be mapped to the at least one consistency level. The probability of each failure class for each consistency level can be summed to determine an expected portion of time that the distributed storage system provides each consistency level.