Layered virtual machine migration algorithm for network resource balancing in cloud computing

doi:10.1007/s11704-016-6135-9

Front. Comput. Sci.

2018, Vol. 12

Issue (1) : 75-85 https://doi.org/10.1007/s11704-016-6135-9

RESEARCH ARTICLE

Layered virtual machine migration algorithm for network resource balancing in cloud computing

Xiong FU^1,²(

), Juzhou CHEN¹, Song DENG³, Junchang WANG¹, Lin ZHANG¹

¹. School of Computer and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
². Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210023, China
³. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

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Abstract

Due to the increasing sizes of cloud data centers, the number of virtual machines (VMs) and applications rises quickly. The rapid growth of large scale Internet services results in unbalanced load of network resource. The bandwidth utilization rate of some physical hosts is too high, and this causes network congestion. This paper presents a layered VM migration algorithm (LVMM). At first, the algorithm will divide the cloud data center into several regions according to the bandwidth utilization rate of the hosts. Then we balance the load of network resource of each region by VM migrations, and ultimately achieve the load balance of network resource in the cloud data center. Through simulation experiments in different environments, it is proved that the LVMMalgorithm can effectively balance the load of network resource in cloud computing.

Keywords virtual machine migration cloud computing layered theory load balancing

Corresponding Author(s): Xiong FU

Just Accepted Date: 23 December 2016 Online First Date: 07 June 2017 Issue Date: 12 January 2018

Cite this article:

Xiong FU,Juzhou CHEN,Song DENG, et al. Layered virtual machine migration algorithm for network resource balancing in cloud computing[J]. Front. Comput. Sci., 2018, 12(1): 75-85.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-016-6135-9
https://academic.hep.com.cn/fcs/EN/Y2018/V12/I1/75

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