MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION FOR RESOURCE ALLOCATION IN CLOUD COMPUTING
Cloud computing is now a hot topic of research that is assumed as the third revolution of IT after computer technology and the internet.In cloud computing field,a service-provider offers large number of resources like computing units,storage space and software etc for customers with a relatively low cost.As the number of customer increases,fulfilling their requirements may become an important yet intractable matter.Resource allocation is therefore a primary issue considered restriction in resource amount that could be afforded by a company.The problem of resource allocation in cloud computing is thought to be a combinatorial optimization problem to a large company for numbers of their customers and owned resources could be huge enough.A particle swarm optimization algorithm is designed for this problem.The algorithm aims at finding out a desired task scheduler on resources based on multiple considerations including total task executing time,resource reservation,and QOS of each task.Pareto-domination mechanism is introduced into the algorithm helping searching multi-objective optimal solutions.Experimental results verify effectiveness and efficiency of the presented algorithm.
cloud computing resource allocation, particle swarm optimization, pareto-dominate
Mingyue Feng Xiao Wang Yongjin Zhang Jianshi Li
Department of Automation Engineering,Military Transportation University,TianJin 300161,China
国际会议
杭州
英文
1607-1611
2012-10-30（万方平台首次上网日期，不代表论文的发表时间）