Volume 7 Number 1 (Jan. 2012)
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JCP 2012 Vol.7(1): 42-52 ISSN: 1796-203X
doi: 10.4304/jcp.7.1.42-52

A New Resource Scheduling Strategy Based on Genetic Algorithm in Cloud Computing Environment

Jianhua Gu, Jinhua Hu, Tianhai Zhao, Guofei Sun
School of Computer, NPU HPC Center, Xi’an, China
Abstract—In view of the load balancing problem in VM resources scheduling, this paper presents a scheduling strategy on load balancing of VM resources based on genetic algorithm. According to historical data and current state of the system and through genetic algorithm, this strategy computes ahead the influence it will have on the system after the deployment of the needed VM resources and then chooses the least-affective solution, through which it achieves the best load balancing and reduces or avoids dynamic migration. At the same time, this paper brings in variation rate to describe the load variation of system virtual machines, and it also introduces average load distance to measure the overall load balancing effect of the algorithm. The experiment shows that this strategy has fairly good global astringency and efficiency, and the algorithm of this paper is, to a great extent, able to solve the problems of load imbalance and high migration cost after system VM being scheduled. What is more, the average load distance does not grow with the increase of VM load variation rate, and the system scheduling algorithm has quite good resource utility.

Index Terms—Computing, virtual machine resources, load balancing, genetic algorithm, scheduling strategy.

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Cite: Jianhua Gu, Jinhua Hu, Tianhai Zhao, Guofei Sun, "A New Resource Scheduling Strategy Based on Genetic Algorithm in Cloud Computing Environment," Journal of Computers vol. 7, no. 1, pp. 42-52, 2012.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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