个人信息Personal Information
副教授
硕士生导师
性别:男
毕业院校:中国科学技术大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:计算机系统结构. 软件工程
办公地点:软件学院综合楼415
联系方式:wfsun@dlut.edu.cn
电子邮箱:wfsun@dlut.edu.cn
SAACO: A Self Adaptive Ant Colony Optimization in Cloud Computing
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论文类型:会议论文
发表时间:2015-08-26
收录刊物:EI、CPCI-S、SCIE、Scopus
页面范围:148-153
关键字:cloud computing; task scheduling; ant colony algorithm; self adaptive
摘要:The cloud environment is a heterogeneous, dynamic and complex environment. The characteristic of Ant Colony Optimization (ACO), such as robustness and self adaptability, can just match the cloud environment. ACO is an algorithm that imitates the ants foraging, and it has a good application in the problems that want to find the optimal solution. The task scheduling in cloud computing is also the problem that want to find the optimal solution actually. In this paper, a self adaptive ant colony optimization (SAACO) is proposed. For the drawback of PACO we proposed before, such as the parameters' selection and the pheromone's update, in SAACO, we use particle swarm optimization (PSO) to make the parameters of ACO to be self adaptive. And we also improve the calculation and update of the pheromone. The results show that SAACO has a better performance than PACO both in makespan and load balance.