FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
GRID codes: Strip-based erasure codes with high fault tolerance for storage systems
ACM Transactions on Storage (TOS)
A performance evaluation and examination of open-source erasure coding libraries for storage
FAST '09 Proccedings of the 7th conference on File and storage technologies
R-ADMAD: high reliability provision for large-scale de-duplication archival storage systems
Proceedings of the 23rd international conference on Supercomputing
An algorithm based mesh check-sum fault tolerant scheme for stream ciphers
International Journal of Communication Networks and Distributed Systems
International Journal of High Performance Computing Applications
A mesh check-sum ABFT scheme for stream ciphers
International Journal of Communication Networks and Distributed Systems
Understanding latent sector errors and how to protect against them
ACM Transactions on Storage (TOS)
Understanding latent sector errors and how to protect against them
FAST'10 Proceedings of the 8th USENIX conference on File and storage technologies
A spin-up saved is energy earned: achieving power-efficient, erasure-coded storage
HotDep'08 Proceedings of the Fourth conference on Hot topics in system dependability
ACM Transactions on Storage (TOS)
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We propose a new fault tolerance metric for XOR-based erasure codes: the minimal erasures list (MEL). A minimal erasure is a set of erasures that leads to irrecoverable data loss and in which every erasure is necessary and sufficient for this to be so. The MEL is the enumeration of all minimal erasures. An XOR-based erasure code has an irregular structure that may permit it to tolerate faults at and beyond its Hamming distance. The MEL completely describes the fault tolerance of an XOR-based erasure code at and beyond its Hamming distance; it is therefore a useful metric for comparing the fault tolerance of such codes. We also propose an algorithm that efficiently determines the MEL of an erasure code. This algorithm uses the structure of the erasure code to efficiently determine the MEL. We show that, in practice, the number of minimal erasures for a given code is much less than the total number of sets of erasures that lead to data loss: in our empirical results for one corpus of codes, there were over 80 times fewer minimal erasures. We use the proposed algorithm to identify the most fault tolerant XOR-based erasure code for all possible systematic erasure codes with up to seven data symbols and up to seven parity symbols.