基于负载均衡策略的块级云存储系统优化

Li Zhou, Yicheng Wang, Jilin Zhang, Jian Wan, Yongjian Ren
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引用次数: 12

摘要

云存储系统利用分布式存储技术和虚拟化技术,为虚拟机客户端提供可定制的存储服务。它们可以分为分布式文件系统和块级存储系统两种类型。Orthrus是轻量级的块级云存储系统,采用多卷服务器架构,避免了其他解决方案中的单点问题。然而,如何使服务器负载均衡成为该体系结构中的一个新问题。本文提出了一种多卷服务器之间的动态负载平衡策略。采用黑盒建模方法对机器性能和负载数量进行表征,并基于遗传算法实现负载均衡策略。大量的实验结果表明,使用多卷服务器时,ORTHRUS的聚合I/O吞吐量显著提高(约2倍),动态负载均衡策略显著提高I/O吞吐量和IOPS(分别约1.8倍和1.2倍)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimize Block-Level Cloud Storage System with Load-Balance Strategy
Cloud storage systems take advantage of distributed storage technology and virtualization technology, to provide virtual machine clients with customizable storage service. They can be divided into two types: distributed file system and block level storage system. Orthrus is a Light weighted Block-Level Cloud Storage System, which adopt multiple volume servers' architecture to avoid single-point problem in other solutions. However, how to make the servers load balance turn into a new problem appears in this architecture. In this paper we present a dynamic load balance strategy between multiple volume servers. We characterize machine capability and load quantity with black box modeling approach, and implement the load balance strategy based on genetic algorithm. Extensive experimental results show that the aggregated I/O throughputs of ORTHRUS are remarkably improved (about two times) with multiple volume servers, and both I/O throughputs and IOPS are remarkably improved (about 1.8 and 1.2 times respectively) by our dynamic load balance strategy.
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