云计算中多层次公平性QoS约束任务调度算法
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摘要
针对传统云任务调度算法只注重执行效率忽略分配公平性的问题,提出了一种满足多重公平性约束的任务调度QoS算法CTS_QFC.该算法利用社会资源分配的公平性理论模型,从用户任务与云资源提供方两个角度,将云任务调度问题建模为一种多重公平性QoS约束模型.第一层QoS按用户QoS偏好对任务分类,并按照任务分类建立一般期望效用函数.第二层QoS定义资源公平性评估函数,评估资源分配的公平性.结果表明,CTS_QFC算法不仅可以确保用户任务的高效执行,还可以提高资源分配与任务调度方案的公平性.
Aiming at the problem that the traditional cloud task scheduling algorithms only pay attention to the execution efficiency with ignoring the fairness of resource allocation,a cloud task scheduling QoS algorithm meeting multiple-level fairness constraints(CTS _QFC) was proposed. With the fairness theory model for the social resource allocation and from two aspects of user tasks and cloud resource providers,the cloud task scheduling problem was modeled as a multiple-level fairness QoS constraint model. The first level QoS classified the tasks according to the QoS preference of users,and established the general expected utility function according to the task classification. The second level QoS defined the resource fairness evaluation function to evaluate the fairness of resource allocation. The results showthat the CTS _QFC algorithm can not only ensure the efficient execution of user tasks,but can also improve the fairness of resource allocation and task scheduling.
Aiming at the problem that the traditional cloud task scheduling algorithms only pay attention to the execution efficiency with ignoring the fairness of resource allocation,a cloud task scheduling QoS algorithm meeting multiple-level fairness constraints(CTS _QFC) was proposed. With the fairness theory model for the social resource allocation and from two aspects of user tasks and cloud resource providers,the cloud task scheduling problem was modeled as a multiple-level fairness QoS constraint model. The first level QoS classified the tasks according to the QoS preference of users,and established the general expected utility function according to the task classification. The second level QoS defined the resource fairness evaluation function to evaluate the fairness of resource allocation. The results showthat the CTS _QFC algorithm can not only ensure the efficient execution of user tasks,but can also improve the fairness of resource allocation and task scheduling.
引文
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[11]邓见光,赵跃龙,袁华强.一种多QoS目标约束的云计算任务调度策略[J].计算机应用研究,2016,33(8):2479-2483.(DENG Jian-guang,ZHAO Yue-long,YUAN Huaqiang.Multi-QoS objective constrainted task scheduling strategy of cloud computing[J].Journal of Computer Application Research,2016,33(8):2479-2483.)
[2]Sobh T,Pourebrahimi B,Ostadzadeh S A,et al.Resource allocation in market-based grids using a historybased pricing mechanism[C]//International Conference on Advances in Computer and Information Sciences and Engineering.M unich,Germany,2008:97-100.
[3]许建豪.云计算中基于拍卖的虚拟机动态供应和分配算法[J].重庆邮电大学学报(自然科学版),2016,28(4):585-592.(XU Jian-hao.Virtual machine dyamic supply and allocation algorithm based on auction in cloud computing[J].Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2016,28(4):585-592.)
[4]Wang W,Liang B,Li B.Multi-resource fair allocation in heterogeneous cloud computing systems[J].IEEETransations on Parallel and Distributed Systems,2015,26(10):2822-2835.
[5]王金海,黄传河,王晶,等.异构云计算体系结构及其多资源联合公平分配策略[J].计算机研究与发展,2015,52(6):1288-1302.(WANG Jin-hai,HUANG Chuan-he,WANG Jing,et al.A heterogeneous cloud computing architecture and multi-resource-joint fairness allocation strategy[J].Journal of Computer Research and Development,2015,52(6):1288-1302.)
[6]Lu D,Ma J,Xi N,et al.A universal fairness evaluation framew ork for resource allocation in cloud computing communications[J].China Communications,2015,12(5):113-122.
[7]卢笛,马建峰,王一川,等.云计算下保障公平性的多资源分配算法[J].西安电子科技大学学报,2014,41(3):162-168.(LU Di,MA Jian-feng,WANG Yi-chuan,et al.Enhanced fairness-based multi-resource allocation algorithm for cloud computing[J].Journal of Xidian University,2014,41(3):162-168.)
[8]薛胜军,胡敏达,许小龙.云环境下公平性优化的资源分配方法[J].计算机应用,2016,36(10):2686-2691.(XUE Sheng-jun,HU Min-da,XU Xiao-long.Fairnessoptimized resource allocation method in cloud environment[J].Journal of Computer Applications,2016,36(10):2686-2691.)
[9]薛胜军,邱爽,许小龙.云环境下能耗感知的公平性提升资源调度策略[J].计算机应用,2016,36(10):2692-2697.(XUE Sheng-jun,QIU Shuang,XU Xiao-long.Energyaw are fairness enhanced resource scheduling mehod in cloud environment[J].Journal of Computer Applications,2016,36(10):2692-2697.)
[10]Li B,Song A,Song J.A distributed QoS-constraint task scheduling scheme in cloud computing environment:model and algorithm[J].Adavance in Information Sciences and Service Sciences,2012,4(5):283-291.
[11]邓见光,赵跃龙,袁华强.一种多QoS目标约束的云计算任务调度策略[J].计算机应用研究,2016,33(8):2479-2483.(DENG Jian-guang,ZHAO Yue-long,YUAN Huaqiang.Multi-QoS objective constrainted task scheduling strategy of cloud computing[J].Journal of Computer Application Research,2016,33(8):2479-2483.)