云环境下结合模糊商空间理论的资源调度算法  

Task Scheduling Algorithm Based on Fuzzy Quotient Space Theory in Cloud Environment

作　　者：齐平[1,2] 李龙澍[1] 

机构地区：[1]安徽大学计算机科学与技术学院,合肥230039 [2]铜陵学院数学与计算机科学系,安徽铜陵244000

出　　处：《小型微型计算机系统》2013年第8期1793-1797,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60273043)资助;安徽省自然科学基金项目(090412054);安徽省科技攻关计划重大科技专项项目(08010201002)资助

摘　　要：考虑到云计算商业化和虚拟化特点,针对云环境中的高效资源调度问题,提出一种基于模糊商空间理论的资源调度算法.在进行资源调度时,算法首先将虚拟机资源抽象为不同的属性信息粒,再根据用户任务QoS特征分层进行粒度融合,最后结合模糊商空间理论建立模糊等价类和距离函数,并据此进行资源匹配.实验结果分析表明,该算法能有效的满足用户任务QoS,提高资源利用率.Considered the commercialization and the virtualization characteristics of cloud computing, focusing on the problem of high efficiency and effectiveness resource scheduling, the paper proposed for the first time an algorithm of resource scheduling based on fuzzy quotient space theory. In the resource scheduling process, each virtual machine attribute is abstracted as an attribute information granulation at first. Then the multi-attribute information granulation according to their granular weight, which are defined by the user QoS requirement is studied. Combining with the theory of fuzzy quotient space, fuzzy equivalence partition and distance function are given at last. Based on this, the matching of tasks with resources in cloud environment is implemented. The experimental results show that the algorithm can effectively execute the user tasks and increase resource utilization rate.

关 键 词：资源调度 模糊商空间 粒度融合 云计算 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]