通信学报2018，Vol.39Issue(1)：56-69,14.DOI:10.11959/j.issn.1000-436x.2018006
多云环境下带截止日期约束的科学工作流调度策略
Scheduling strategy for science workflow with deadline constraint on multi-cloud
摘要
Abstract
In view of the deadline-constrained scientific workflow scheduling on multi-cloud,an adaptive discrete particle swarm optimization with genetic algorithm (ADPSOGA) was proposed,which aimed to minimize the execution cost of workflow while meeting its deadline constrains.Firstly,the data transfer cost,the shutdown and boot time of virtual machines,and the bandwidth fluctuations among different cloud providers were considered by this method.Secondly,in order to avoid the premature convergence of traditional particle swarm optimization (PSO),the randomly two-point crossover operator and randomly one-point mutation operator of the genetic algorithm (GA) was introduced.It could effectively improve the diversity of the population in the process of evolution.Finally,a cost-driven strategy for the deadline-constrained workflow was designed.It both considered the data transfer cost and the computing cost.Experimental resuits show that the ADPSOGA has better performance in terms of deadline and cost reducing in the fluctuant environment.关键词
云计算/截止日期约束/工作流调度/波动性Key words
cloud computing/deadline constraint/workflow scheduling/fluctuation分类
信息技术与安全科学引用本文复制引用
林兵,郭文忠,陈国龙..多云环境下带截止日期约束的科学工作流调度策略[J].通信学报,2018,39(1):56-69,14.基金项目
国家重点研发计划基金资助项目(No.2017YFB1002000) （No.2017YFB1002000）
国家自然科学基金资助项目(No.61672159) （No.61672159）
福建省科技创新平台计划基金资助项目(No.2009J1007,No.2014H2005) （No.2009J1007,No.2014H2005）
海峡政务大数据应用省级协同创新中心基金资助项目 （）
The National Key R&D Program of China (No.2017YFB1002000),The National Natural Science Foundation of China (No.61672159),The Technology Innovation Platform Project of Fujian Province (No.2009J1007,No.2014H2005),The Foundation of The Fujian Collaborative Innovation Center for Big Data Application in Governments （No.2017YFB1002000）
