An ACO-LB algorithm for task scheduling in the cloud environment

被引：31

作者：

Xue, Shengjun ^{[1
,2
]}

Li, Mengying ^{[1
]}

Xu, Xiaolong ^{[1
]}

Chen, Jingyi ^{[1
]}

机构：

[1] Nanjing University of Information Science and Technology, School of Computer and Software, Nanjing

[2] Nanjing University of Information Science and Technology, Jiangsu Engineering Center of Network Monitoring, Nanjing

来源：

Journal of Software | 2014年 / 9卷 / 02期

关键词：

ACO (Ant colony optimization); ACO-LB; Cloud computing; Load balancing; Task scheduling;

D O I：

10.4304/jsw.9.2.466-473

中图分类号：

学科分类号：

摘要：

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. © 2014 ACADEMY PUBLISHER.

引用

页码：466 / 473

页数：7

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