Genetic Algorithm and Ant Colony Algorithm Based Energy-Efficient Task Scheduling

被引：0
|
作者：
Zhao, Jianfeng [1 ]
Qiu, Hongze [1 ]
机构：
[1] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Shandong, Peoples R China
来源：
2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (ICIST) | 2013年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Task Scheduling is a critical problem in cloud computing platforms. Traditional algorithms mainly focus on shortening the makespan, but seldom mention the energy consumption. This paper proposes a duplication based method to reach multiple targets, including reducing the executing time and energy cost. The main algorithms used are genetic algorithm and ant colony algorithm, with a new dynamic fusion strategy proposed to gain the optimal solution quickly.
引用
收藏
页码：946 / 950
页数：5
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