RAFI: Risk-Aware Failure Identification to Improve the RAS in Erasure-coded Data Centers
RAFI: Risk-Aware Failure Identification to Improve the RAS in Erasure-coded Data Centers
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发表时间：
2018
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通讯作者：
Juntao Fang;Shenggang Wan;Xubin He
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作者：
Juntao Fang;Shenggang Wan;Xubin He
数据的可靠性和可用性以及擦除编码数据中心的可用性（RAS）受节点失败引起的数据修复的影响很大。与对数据修复的恢复阶段进行了广泛研究和优化的恢复阶段相比，数据修复的故障识别阶段的研究较少。此外，在传统的失败识别方案中，所有块都具有相同的识别时间阈值，因此失去了进一步改善RAS的机会。为了解决这个问题，我们提出了Rafi，这是一种新型的风险瓦失败识别方案。在拉菲（Rafi）中，使用不同的时间阈值来识别出不同数量的失败块的条纹中的块故障。对于那些处于高风险条纹的块（块有许多失败的条纹），采用了较短的识别时间，从而提高了整体数据可靠性和可用性。对于那些处于低风险条纹的块（仅少数失败的块），采用了更长的识别时间，从而减少了维修网络流量。因此，可以同时改进RA。我们使用模拟和原型实施来评估Rafi。从广泛的模拟中收集的结果证明了Rafi在改善RAS方面的有效性和效率。我们对HDFS实施原型，以验证正确性并评估RAFI的计算成本。
Data reliability and availability, and serviceability (RAS) of erasure-coded data centers are highly affected by data repair induced by node failures. Compared to the recovery phase of the data repair, which is widely studied and well optimized, the failure identification phase of the data repair is less investigated. Moreover, in a traditional failure identification scheme, all chunks share the same identification time threshold, thus losing opportunities to further improve the RAS. To solve this problem, we propose RAFI, a novel riskaware failure identification scheme. In RAFI, chunk failures in stripes experiencing different numbers of failed chunks are identified using different time thresholds. For those chunks in a high risk stripe (a stripe with many failed chunks), a shorter identification time is adopted, thus improving the overall data reliability and availability. For those chunks in a low risk stripe (one with only a few failed chunks), a longer identification time is adopted, thus reducing the repair network traffic. Therefore, the RAS can be improved simultaneously. We use both simulations and prototyping implementation to evaluate RAFI. Results collected from extensive simulations demonstrate the effectiveness and efficiency of RAFI on improving the RAS. We implement a prototype on HDFS to verify the correctness and evaluate the computational cost of RAFI.