CRMS: A centralized replication management scheme for cloud storage system

Kangxian Huang, Dagang Li, Yongyue Sun
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引用次数: 6

Abstract

As distributed storage clusters have been used more and more widely in recent years, data replication management, which is the key to data availability, has become a hot research topic. In storage clusters, internal network bandwidth is usually a scarce resource. Misplaced replicas may take up too much network bandwidth and greatly deteriorate the overall performance of the cluster. Aiming to reduce the internal network traffic and to improve load balancing of distributed storage clusters, we developed a centralized replication management scheme referred to as CRMS. A model is proposed to capture the relationships of block access probability, replica location and network traffic. Based on this model, the replica placement problem is formulated as a 0-1 programming optimization problem. Based on the feasible solution to this problem, a heuristic is proposed to process the replica adjustments step by step. Our CRMS is evaluated by using the access history from a distributed storage cluster of Xunlei Inc., one of the leading Internet companies in China. The experimental results show that CRMS can greatly reduce the amount of internal network bandwidth consumption, while keeping the cluster's storage usage in balance.
CRMS:云存储系统的集中复制管理方案
近年来,随着分布式存储集群的应用越来越广泛,作为数据可用性关键的数据复制管理成为研究的热点。在存储集群中,内部网络带宽通常是一种稀缺资源。放错位置的副本可能会占用过多的网络带宽,并大大降低集群的整体性能。为了减少内部网络流量并改善分布式存储集群的负载平衡,我们开发了一种集中式复制管理方案,称为CRMS。提出了一个模型来捕捉块访问概率、副本位置和网络流量之间的关系。在此模型的基础上,将副本放置问题表述为一个0-1规划优化问题。基于该问题的可行解,提出了一种启发式算法,对副本调整进行分步处理。我们的crm是通过使用迅雷公司(中国领先的互联网公司之一)的分布式存储集群的访问历史来评估的。实验结果表明,CRMS可以在保持集群存储使用平衡的同时,大大减少内部网络带宽的消耗。
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