An efficient load balancing algorithm for virtual machine allocation based on ant colony optimization

Peng Xu, Guimin He, Zhenhao Li and Zhongbao Zhang

International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 12, 1550147718793799

Abstract: With the rapid development of information technologies and the popularization of Internet applications, more and more companies and developers pay great attention to the cloud computing. As one of the most significant problems in cloud computing, virtual machine allocation has attracted significant attention. However, early studies usually ignore the load balance issue of the resources. In this article, we aim at multidimensional resource load balancing of all the physical machines in the cloud computing platform to maximize the utilization of resources. To achieve this goal, we leverage the ant colony optimization to design an efficient virtual machine allocation algorithm based on the NP-hard feature of this problem. Specifically, we customize the ant colony optimization in the context of virtual machine allocation and introduce an improved physical machine selection strategy to the basic ant colony optimization in order to prevent the premature convergence or falling into the local optima. Through extensive simulations, we demonstrate that our proposed algorithm can effectively achieve load balancing in virtual machine allocation and improve resource utilization for the cloud computing platform.

Keywords: Cloud computing; load balance; virtual machine allocation; ant colony optimization; pheromone (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:12:p:1550147718793799

DOI: 10.1177/1550147718793799

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