A Decentralized Virtual Machine Migration Approach of Data Centers for Cloud Computing

Xiaoying Wang, Xiaojing Liu, Lihua Fan and Xuhan Jia

Mathematical Problems in Engineering, 2013, vol. 2013, 1-10

Abstract:

As cloud computing offers services to lots of users worldwide, pervasive applications from customers are hosted by large-scale data centers. Upon such platforms, virtualization technology is employed to multiplex the underlying physical resources. Since the incoming loads of different application vary significantly, it is important and critical to manage the placement and resource allocation schemes of the virtual machines (VMs) in order to guarantee the quality of services. In this paper, we propose a decentralized virtual machine migration approach inside the data centers for cloud computing environments. The system models and power models are defined and described first. Then, we present the key steps of the decentralized mechanism, including the establishment of load vectors, load information collection, VM selection, and destination determination. A two-threshold decentralized migration algorithm is implemented to further save the energy consumption as well as keeping the quality of services. By examining the effect of our approach by performance evaluation experiments, the thresholds and other factors are analyzed and discussed. The results illustrate that the proposed approach can efficiently balance the loads across different physical nodes and also can lead to less power consumption of the entire system holistically.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:878542

DOI: 10.1155/2013/878542

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