Volume 9 Number 2 (Feb. 2014)
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JSW 2014 Vol.9(2): 466-473 ISSN: 1796-217X
doi: 10.4304/jsw.9.2.466-473

An ACO-LB Algorithm for Task Scheduling in the Cloud Environment

Shengjun Xue1, Mengying Li1, Xiaolong Xu1, Jingyi Chen1, Shengjun Xue2
1Nanjing University of Information Science & Technology, School of Computer and Software, Nanjing, China
2Nanjing University of Information Science & Technology, Jiangsu Engineering Center of Network Monitoring, Nanjing, China

Abstract—In the face of a large number of task requests which are submitted by users, the cloud data centers need not only to finish these massive tasks but also to satisfy the user's service demand. How to allocate virtual machine reasonably and schedule the tasks efficiently becomes a key problem to be solved in the cloud environment. This paper proposes a ACO-LB(Load balancing optimization algorithm based on ant colony algorithm) algorithm to solve the load imbalance of virtual machine in the process of task scheduling .The ACO-LB algorithm can adapt to the dynamic cloud environment. It will not only shorten the makespan of task scheduling, but also maintain the load balance of virtual machines in the data center. In this paper, the workflow scheduling is simulated in CloudSim. The results show that the proposed ACO-LB algorithm has better performance and load balancing ability.

Index Terms—cloud computing, task scheduling, ACO (Ant colony optimization), ACO-LB, Load Balancing

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Cite: Shengjun Xue, Mengying Li, Xiaolong Xu, Jingyi Chen, Shengjun Xue, "An ACO-LB Algorithm for Task Scheduling in the Cloud Environment," Journal of Software vol. 9, no. 2, pp. 466-473, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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