Abstract
RAID, as a popular technology to improve the performance and reliability of storage system, has been used widely in computer industry. Recently, the technique of designing data layout in order to fit the requirements of networked storage is becoming a new challenge in this field. In this paper, we present a double-objective Genetic Algorithm for parity declustering optimization in networked RAID with a modified NSGA, we also take Distributed recovery workload and Distributed parity as two objects to find optimal data layout for parity declustering in networked RAID. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Liu, X., Wang, G., & Liu, J. (2007). A double-objective genetic algorithm for parity declustering optimization in networked RAID. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4494 LNCS, pp. 415–420). Springer Verlag. https://doi.org/10.1007/978-3-540-72905-1_37
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