A double-objective genetic algorithm for parity declustering optimization in networked RAID

Authors:
Xiaoguang Liu;Gang Wang;Jing Liu
Affiliations:
Department of Computer Science, Nankai University, Tianjin, China;Department of Computer Science, Nankai University, Tianjin, China;Department of Computer Science, Nankai University, Tianjin, China
Venue:
ICA3PP'07 Proceedings of the 7th international conference on Algorithms and architectures for parallel processing
Year:
2007

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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.