Abstract
The virtual machine placement is closely related to the efficient and balanced utilization of physical resources. In this paper, the influence of two scenarios about resource utilization on load balancing is analyzed. A multi-objective ant colony optimization algorithm is proposed to solve the virtual machine placement problem, which balances the load among physical machines and the internal load of physical machine simultaneously. The proposed algorithm is compared with two single objective ant colony optimization algorithms, first fit algorithm and greedy algorithm under some instances. The results show that the proposed algorithm can search and find solutions that exhibit good balance among objectives while others cannot. This demonstrates the proposed algorithm can balance the load in the process of mapping virtual machines to physical machines.
Highlights
Cloud computing [1] as a new service model can effectively cope with mass data processing and computing needs by integrating Internet resources
Cloud computing [2] can be roughly classified into three types according to the service type: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS)
The high load will affect the performance of upper applications, and the low load will not make full use of the limited resources, so optimal virtual machine placement closely related to the balanced utilization of resources is very important
Summary
Cloud computing [1] as a new service model can effectively cope with mass data processing and computing needs by integrating Internet resources. The high load will affect the performance of upper applications, and the low load will not make full use of the limited resources, so optimal virtual machine placement closely related to the balanced utilization of resources is very important. In [15], a multi-objective ant colony system algorithm for virtual machine placement in cloud computing is proposed to minimize resource wastage and power consumption. The designed algorithm in this paper is to make the utilization of physical machine resources as balanced as possible, so more needs are met under the condition of limited resources. Multi-objective ant colony algorithm for load balancing is proposed in detail to solve the problem.
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