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Parallel Data Regeneration Based on Multiple Trees with Network Coding in Distributed Storage System

机译:分布式存储系统中基于网络编码的多树并行数据再生

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Distributed storage systems can provide large-scale data storage and high data reliability by redundant schemes, such as replica and erasure codes. Redundant data may get lost due to frequent node failures in the system. The lost data is needed to be regenerated as soon as possible so as to maintain data availability and reliability. The direct way for reducing regeneration time is to reduce network traffic in regeneration. Compared with that way, tree-structured regeneration achieves shorter regeneration time by constructing better tree-structured topology to increase transmission bandwidth. However, some bandwidth of many other edges beyond the tree is not utilized to speed up transmission in tree-structured regeneration. In this paper, we consider to use multiple edge-disjoint trees to parallel regenerate the lost data, and analyze the total regeneration time. We deduce the formula about optimal regeneration time, and propose an approximate construction algorithm with polynomial time complexity for the optimal multiple regeneration trees. Our experiments shows, the regeneration time reduces 62 % compared with common tree-structured scheme, and the file availability reaches almost 99 %.
机译:分布式存储系统可通过冗余方案(例如副本和擦除码)提供大规模数据存储和高数据可靠性。由于系统中频繁发生节点故障,冗余数据可能会丢失。需要尽快重新生成丢失的数据,以保持数据的可用性和可靠性。减少再生时间的直接方法是减少再生中的网络流量。与之相比,树状结构的再生通过构建更好的树状结构的拓扑来增加传输带宽,从而缩短了再生时间。但是,树以外的许多其他边缘的某些带宽未用于加速树结构再生中的传输。在本文中,我们考虑使用多个边缘不相交的树来并行地重新生成丢失的数据,并分析总的重新生成时间。我们推导了最佳再生时间的公式,并提出了一种具有多项式时间复杂度的近似构造算法,用于优化多个再生树。我们的实验表明,与普通的树状结构方案相比,再生时间减少了62%,文件可用性几乎达到了99%。

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