A novel replica placement algorithm for minimising communication cost in distributed storage platform. (3rd March 2020)

• Record Type: Journal Article
• Authors: Liu, Changsong
• Is Part Of: International journal of networking and virtual organisations. Volume 22:Number 2(2020)
• Page Start: 147
• Page End: 161
• Publication Date: 2020-03-03
• Subjects: data replication -- replica service -- distributed storage -- cloud computing; Computer networks -- Periodicals; Information networks -- Periodicals; Virtual corporations -- Periodicals; Electronic commerce -- Periodicals; Management information systems -- Periodicals; Management -- Data processing -- Periodicals; 004.65
• Languages: English
• ISSNs: 1470-9503

Abstract

In large-scale distributed systems, replication service has been playing a critical role to improve the availability and reliability of user data. Conventionally, the existing replication services mainly concentrate on how many replicas are needed to maintain desirable availability and reliability rather than how to place replicas on the most suitable storage nodes. As a result, the communication-related costs when accessing data are significantly increased, which in turn degrades the execution performance of user applications. In this paper, we propose a novel replica placement algorithm which is designed to minimise the communication cost when accessing or managing replicas in a large-scale storage platform. In the proposed algorithm, the replica placement problem is formulised a classical multi-knapsack problem, and two heuristic metrics are introduced to obtain the sub-optimal solution of this problem. A lot of experiments are conducted to investigate the performance of the proposed algorithm. The experimental results indicate that our replica placement algorithm outperforms many existing approaches in terms of different performance metrics. In addition, the proposed algorithm can also significantly improve the execution efficiency for data-intensive applications, which are very common in nowadays large-scale distributed systems, such as grid and cloud.