2023
DOI: 10.1109/access.2023.3267106
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Optimized Proactive Recovery in Erasure-Coded Cloud Storage Systems

Abstract: Cloud data centers have started utilizing erasure coding in large-scale storage systems to ensure high reliability with limited overhead compared to replication. However, data recovery in erasure coding incurs high network bandwidth consumption compared to replication. Cloud storage systems also play an important role in the energy consumption of data centers. Heuristic proactive recovery algorithms select all data blocks from failure-predicted disk/machine and perform proactive replication that contributes to… Show more

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Cited by 3 publications
(1 citation statement)
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“…If the damaged data is accessed, degraded data reading may occur, resulting in the increased response time. The predictive repair is to process the possible damaged or lost data blocks in advance before the actual failure based on the prediction of the soon-to-fail (STF) node through machine learning or other methods [11], [12], [13], [14], [15], so as to shorten the unavailable time of data blocks and improve data reliability [16], [17], [18], [19], [20], [21]. However, the above researches focus on how to optimize the repair process and ignore whether it is necessary to immediately repair faults.…”
Section: Introductionmentioning
confidence: 99%
“…If the damaged data is accessed, degraded data reading may occur, resulting in the increased response time. The predictive repair is to process the possible damaged or lost data blocks in advance before the actual failure based on the prediction of the soon-to-fail (STF) node through machine learning or other methods [11], [12], [13], [14], [15], so as to shorten the unavailable time of data blocks and improve data reliability [16], [17], [18], [19], [20], [21]. However, the above researches focus on how to optimize the repair process and ignore whether it is necessary to immediately repair faults.…”
Section: Introductionmentioning
confidence: 99%