Chemical reaction optimization for virtual machine placement in cloud computing

摘要

With the development of virtualization technologies, cloud data centers are faced with more and more virtual machines (VMs) requests. How to realize an efficient virtual machine placement (VMP) becomes a hot research topic. The optimal resource consumption and the utilization rate of a physical machine in the whole cloud data center can be realized by optimizing the process from the virtual machine to the physical machine. VMP is a combinatorial optimization problem which was demonstrated to be NP-hard. In this paper, a new formulation of VMP problem is presented by taking into consideration the optimization of the two following objectives: (i) minimize the energy consumption, and (ii) maximize the resource utilization. In order to achieve these targets, we propose two algorithms based on chemical reaction optimization (CRO) algorithm, namely CVP and CVV, with two types of solution representation. The proposed algorithms are compared with other optimal placement strategies, namely Cuckoo Search Optimization (CSO), Reordered Grouping Genetic Algorithm (RGGA), First Fit Decreasing (FFD) and Best Fit Decreasing (BFD). Experimental results show that the proposed CVP and CVV give better performance comparing with the other compared algorithms in terms of resource consumption and resource utilization. In term of scalability, the proposed CVV algorithm benefits from the high computational speed and performs well when there are a large number of virtual machine scheduling requests in the cloud data center.