标题：Genetic Algorithm and Ant Colony Algorithm Based Energy-Efficient Task Scheduling
作者：Zhao, Jianfeng; Qiu, Hongze
作者机构：[Zhao, Jianfeng; Qiu, Hongze] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Shandong, Peoples R China.
会议名称：International Conference on Information Science and Technology (ICIST)
会议日期：MAR 23-25, 2013
来源：2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (ICIST)
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.