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An Efficient Group-based Data Backup and Recovery Scheme in Cloud Computing Systems

摘要


In cloud computing systems with huge volumes of data, fault tolerance is of critical importance. To enhance data fault tolerance in cloud systems, we introduce a new group-based data backup and recovery scheme in this paper. The new scheme performs efficient diskless checkpointing practices to maintain data correctness via alternative processors upon processor failure. The basic idea is to place six processors in a transmission group, with each processor sending data to only two member processors. In face of processor failure, such a practice helps reduce the needed data backup volume and recovery time, and reaches up to 3/6 fault-tolerance ratios. Our scheme attains the performance gain mainly because (1) it allows a processor to receive only two backup data from the group - each processor hence performs only one XOR during data backup, and (2) all groups work independently in parallel so that the needed data backup and recovery time is reduced to that for a single group. To compare the performance of our scheme and related schemes, we carry out extended simulation runs with results indicating improved survival counts, fault-tolerance ratios and computation overhead for our scheme.

被引用紀錄


Huang, C. W. (2014). 嵌入式記憶體系統之效能與耗能優化 [doctoral dissertation, National Chiao Tung University]. Airiti Library. https://doi.org/10.6842/NCTU.2014.01110
Wang, H. F. (2014). 微處理器核心熱分布量測與模擬平台之建構 [master's thesis, National Chiao Tung University]. Airiti Library. https://doi.org/10.6842/NCTU.2014.01087
Ho, C. C. (2016). 超大規模快閃記憶體儲存裝置之效能、模組化和可靠度技術探討 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU201600610
Fang, H. W. (2014). 針對快閃記憶體耐久性之資料索引、搜尋及回復策略 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2014.02945
Chang, Y. H. (2009). 快閃記憶體儲存系統耐用度提昇之高效能管理策略 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2009.00389

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