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Journal of Software:2013.24(8):1937-1946

云计算虚拟资源的熵优化和动态加权评估模型
左利云,曹志波,董守斌
(广东省石化装备故障诊断重点实验室(广东石油化工学院), 广东 茂名 525000;广东省计算机网络重点实验室(华南理工大学), 广东 广州 510641)
Virtual Resource Evaluation Model Based on Entropy Optimized and Dynamic Weighted in Cloud Computing
ZUO Li-Yun,CAO Zhi-Bo,DONG Shou-Bin
(Guangdong Province Key Laboratory of Petrochemical Equipment Fault Diagnosis (Guangdong University of Petrochemical Technology), Maoming 525000, China;Guangdong Province Key Laboratory of Computer Network (South China University of Technology), Guangzhou 510641, China)
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Received:June 19, 2012    Revised:December 27, 2012
> 中文摘要: 云资源的动态变化和不确定性给资源管理及任务调度带来了很大的困难.为了准确地掌握资源动态负载和可用能力信息,提出一种基于熵优化和动态加权的资源评估模型,其中,熵优化模型利用最大熵和熵增原理的目标函数及约束条件,筛选出满足用户QoS 和系统最大化的资源,实现最优调度,保障用户QoS.对筛选后的资源再进行动态加权负载评估,对负载过重及长期不可用资源进行迁移、释放等,可减少能耗,实现负载均衡和提高系统利用率.设计了仿真实验,以验证所提评估模型的性能.实验结果表明,熵优化模型对用户QoS 和系统最大化有很好的效果,动态加权负载评估有利于均衡负载,提高系统利用率.该评估模型实现了用户QoS 保障、减少能耗、负载均衡以及提高系统利用率等多目标的优化.
Abstract:The dynamic and uncertainty of cloud resource makes resource allocation and task scheduling more difficult. In order to retrieve accurate resource information about dynamic loads and available capacity, this study proposes a resource evaluation model based on entropy optimization and dynamic weighting. The entropy optimization filters the resources that satisfy user QoS and system maximization by goal function and constraints of maximum entropy and the entropy increase principle, which achieves optimal scheduling and satisfied user QoS. Then the evaluation model evaluates the load of having filtered resources by dynamic weighted algorithm. In order to reduce energy consumption, achieve load balancing and improve system utilization, the study allows the migration or release the resources which overload and unavailable for a long time. Experimental results show the effect of entropy optimization on user QoS and system maximization, and dynamic weighted algorithm benefits load balancing and system utilization. The experimental results prove that the evaluation model achieves multi-objective optimization such as satisfying user QOS, reducing energy assumption, balancing load, improving system utilization and so on.
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基金项目:国家自然科学基金(61070092) 国家自然科学基金(61070092)
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左利云,曹志波,董守斌.云计算虚拟资源的熵优化和动态加权评估模型.软件学报,2013,24(8):1937-1946

ZUO Li-Yun,CAO Zhi-Bo,DONG Shou-Bin.Virtual Resource Evaluation Model Based on Entropy Optimized and Dynamic Weighted in Cloud Computing.Journal of Software,2013,24(8):1937-1946