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CubicRing: Exploiting Network Proximity for Distributed In-Memory Key-Value Store

机译:CubicRing:利用网络邻近性来分布内存中的键值存储

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In-memory storage has the benefits of low I/O latency and high I/O throughput. Fast failure recovery is crucial for large-scale in-memory storage systems, bringing network-related challenges, including false detection due to transient network problems, traffic congestion during the recovery, and top-of-rack switch failures. In order to achieve fast failure recovery, in this paper, we present CubicRing, a distributed structure for cube-based networks, which exploits network proximity to restrict failure detection and recovery within the smallest possible one-hop range. We leverage the CubicRing structure to address the aforementioned challenges and design a network-aware in-memory key-value store called MemCube. In a 64-node 10GbE testbed, MemCube recovers 48 GB of data for a single server failure in 3.1 s. The 14 recovery servers achieve 123.9 Gb/s aggregate recovery throughput, which is 88.5% of the ideal aggregate bandwidth and several times faster than RAMCloud with the same configurations.
机译:内存中存储具有低I / O延迟和高I / O吞吐量的优势。快速故障恢复对于大规模内存存储系统至关重要,它带来了与网络相关的挑战,包括由于瞬态网络问题导致的错误检测,恢复期间的流量拥塞以及机架顶交换机故障。为了实现快速故障恢复,在本文中,我们介绍了CubicRing,这是一种基于多维数据集的网络的分布式结构,该结构利用网络邻近性将故障检测和恢复限制在最小的单跳范围内。我们利用CubicRing结构来解决上述挑战,并设计一种称为MemCube的网络感知内存中键值存储。在64节点10GbE测试平台中,MemCube在3.1 s内因单个服务器故障而恢复了48 GB数据。 14台恢复服务器实现了123.9 Gb / s的聚合恢复吞吐量,是理想聚合带宽的88.5%,比具有相同配置的RAMCloud快几倍。

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