Improved GEP Algorithm for Task Scheduling in Cloud Computing

摘要：

　　Since the resources stored in the cloud is huge and the cost of each task in cloud resources is different,the simple Round Robin algorithm and FIFO algorithm for task scheduling cant met the growing scale of cloud computing.The traditional GA algorithm for task scheduling,which has the defect of premature convergence,only takes the time cost into consideration,but ignores the consumption of resources.In order to solve the problems exists in multi-task scheduling in cloud computing mentioned above,we propose an improved GEP algorithm with double fitness functions(DF-GEP),and also constructs a new ETCC matrix which not only considers the running time of all tasks,but also takes the running cost of the tasks into consideration.This improved algorithm reduces the optimization time,and falls into the local optimal solution hardly at the same time.This improved algorithm expresses a good convergence,through experiments compared with GA and ordinary GEP algorithm by using the Map/Reduce programming model.

关键词： Cloud Computing GEP Algorithm ETC Matrix Task Scheduling

作者: LI Kun-lun Wang Jun Song Jian Dong Qing-yun

作者单位: College of Electronic and Information Engineering Hebei University Baoding,China

会议类型: 国际会议

会议名称: 2014 2nd International Conference on Advanced Cloud and Big Data (CBD 2014)(2014年先进云计算和大数据国际会议)

会议地点: 安徽黄山

会议语种:英文

页码: 93-99

在线出版日期: 2014-11-20（万方平台首次上网日期，不代表论文的发表时间）