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Improve Throughput of Storage Cluster Interconnected with a TCP/IP Network Using Intelligent Server Grouping

机译:使用智能服务器分组功能提高与TCP / IP网络互连的存储集群的吞吐量

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Cluster-based storage systems connected with TCP/IP networks are expected to achieve a high throughput by striping files across multiple storage servers. However, for the storage system interconnected with the TCP/IP network, several critical issues, like Incast effect and data access interference, invalidate the assumption that higher access parallelism always results in increased I/O throughput. To address this issue, we propose a new file striping strategy, named as storage server grouping (SSG), which changes file striping pattern across the storage servers based on the analysis of file popularity and impact of the number of storage servers on the clients' perceived performance (I/O speedup) to reduce the interference of data accesses to popular files and avoid dramatic reduction of system throughput caused by the Incast effect. Our experimental evaluation shows that SSG can improve I/O throughput by 22.1% on average.
机译:与TCP / IP网络连接的基于群集的存储系统有望通过跨多个存储服务器分割文件来实现高吞吐量。但是,对于与TCP / IP网络互连的存储系统,一些关键问题(如Incast效应和数据访问干扰)使以下假设无效:较高的访问并行性总是导致I / O吞吐量增加。为解决此问题,我们提出了一种新的文件条带化策略,称为存储服务器分组(SSG),它基于对文件受欢迎程度的分析以及存储服务器数量对客户端的影响来更改整个存储服务器上的文件条带化模式。感知性能(I / O加速),以减少对流行文件的数据访问干扰,并避免因Incast效应而导致的系统吞吐量急剧下降。我们的实验评估表明,SSG可以平均将I / O吞吐量提高22.1%。

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