Computer Engineering and Applications ›› 2014, Vol. 50 ›› Issue (19): 70-73.

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Research of cloud resource allocation based on Pareto optimality

BIAN Genqing, ZHANG Wenjing, SHAO Bilin, GONG Peijiao   

  1. School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
  • Online:2014-10-01 Published:2014-09-29



  1. 西安建筑科技大学 信息与控制工程学院,西安 710055

Abstract: In the cloud environment, service resources are hard to realize the optimal dynamic allocation in each user. The paper combines Pareto optimality theory and particle swarm optimization algorithm with each other which have applied in the cloud computing model about the above problem, to optimization configuration for the utility of various service resources, and finally make the utilization rate of resources achieve an optimal state, and make a simulation experiment of cloud service resources scheduling through CloudSim. The results show that the cloud computing model adopted Pareto optimality algorithm has better performance than before, and the configuration of resources has been achieved the optimal.

Key words: cloud computing, Pareto optimality, service resource, particle swarm optimization algorithm

摘要: 针对在云环境中,服务资源在各用户间难以实现最优动态分配的问题,利用帕累托最优理论与粒子群优化算法相互结合应用于云计算模型中,对各种服务资源的效用进行最优化配置,最终使资源利用率达到一个最优的状态。通过CloudSim对云服务资源调度进行仿真实验,结果表明,采用帕累托最优算法优化后的云计算模型具有更好的系统性能,使得资源的调度和配置达到最优。

关键词: 云计算, 帕累托最优, 服务资源, 粒子群优化算法