一种高效云任务调度博弈算法  

An Efficient Cloud Tasks Scheduling Game Algorithm

作　　者：段昌敏[1] 沈济南[1,2] 周慧华[1] DUAN Chang-min SHEN Ji-nan ZHOU Hui-hua(School of Information and Engineering, Hubei University for Nationalities, Enshi 445000, China School of Computer Science and Technology, Huazhong University o5 Science and Teehnology,Wuhan 430074,China)

机构地区：[1]湖北民族学院信息工程学院,湖北恩施445000 [2]华中科技大学计算机科学与技术学院,湖北武汉430074

出　　处：《微电子学与计算机》2017年第3期40-45,共6页Microelectronics & Computer

基　　金：国家自然科学基金(61262078);湖北省自然科学基金(2015CFC783)

摘　　要：为了更加高效安全的进行云任务调度,提出一种考虑资源可靠性的云任务调度博弈算法.该算法将任务执行代价、资源利用代价、安全可信代价和负载均衡代价综合考虑到博弈效用函数中,以最优化博弈效用函数为目标,将云任务调度问题形式化为非合作博弈模型进行求解.算法求解过程划分为两个层次,并分别利用GA算法和改进MCT算法对其进行求解,最终得到非合作博弈的纳什均衡.实验结果表明,算法在保证任务完成时间和任务响应时间的同时,可以降低任务执行的失效率,并在不降低负载均衡度的情况下以较快的收敛速度整体提高任务执行效率.For implementing efficiently and safely cloud tasks scheduling, a task scheduling game alogrithm considering resource reliability is presented in this paper. Tasks execution cost, resource utilization cost , sacurity cost and load balance cost are considered comprehensively in the game＇ s utility function in our algorithm. With optimizing the game＇s utility function as the goal, cloud tasks scheduling problem is formalized as a non-cooperative game model. This solving process is divided into two level. GA and improved MCT are used to solve the two level respectively, which enventually leads to get Nash equilibrium of non-cooperative game. Experimental results shows that our algorithm not only can guarantee task completion time and task response time, but can reduce the failure rate of task execution and improve the task execution efficiency integrally without reducing load balance degree and with a faster convergence.

关 键 词：云计算 任务调度 博弈 效用函数 负载均衡 

分 类 号：TP393.1[自动化与计算机技术—计算机应用技术]