摘要
为了快速找到较优的调度方案,针对时间约束工作流调度问题,即能在满足用户的截止时间约束的条件下最小化调度费用,提出基于粒子群算法的最优调度方案搜索方法。利用关键路径进行粒子初始化和搜索阶段的筛选处理,不但能够显著提高搜索结果的精度,而且减少了搜索的计算时间。将改进算法和传统粒子群优化算法进行了实验评估对比,实验数据证明,使用该方法使粒子搜索的时间少于传统粒子群算法,并且结果也优于传统方法。
To get the optimal scheduling scheme quickly,aiming at the problem of scheduling time constrained cloud workflow which was minimized the total computing cost under the user＇s temporal constraint,a searching method of optimal scheduling solution based on Particle Swarm Optimization（PSO）algorithm was proposed.Owing to the problems such as random particles of traditional PSO algorithm and low search speed during the iteration,the critical path was used to select particle initialization and search space during the iterations,which was not only improved the searching accuracy,but also reduce the computing time.Compared with the traditional PSO,the experiment results proved that the proposed approach could achieve better performance with less computation time.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2016年第2期372-380,共9页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(61173097
61202202)
浙江省重大科技专项重大工业资助项目(2013C01112)
杭州市重大科技创新专项资助项目(20132011A16)~~
关键词
工作流调度
粒子群算法
关键路径
云计算
workflow scheduling
particle swarm optimization
critical paths
cloud computing
