MRMS: A MOEA-based replication management scheme for cloud storage system

As distributed storage clusters have been used more and more widely in recent years, data replication management 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. Based on multi-objective evolutionary algorithm(MOEA), we developed a replication management scheme to improve performance by reducing internal network traffic and balancing load of storage clusters. The replica placement problem is formulated as some multi-objective programming optimization problems and solved by MOEA to get a Pareto solution set. Based on the average access time, a method is proposed to pick out the suitable solution from the set. Those suitable solutions are gathered to form the final replica location. Then we propose a method to make adjustments step by step according to the replica location. A method to reduce problem size is also proposed. MRMS is evaluated by the access history from a distributed storage cluster of Xunlei Inc. The experimental results show that MRMS can effectively improve the overall performance of the storage cluster.