Optimal methods for virtual machine scheduling with uncertain execution times in cloud

摘要：

　　In cloud computing,execution times of tasks or jobs on virtual machines are usually uncertain.To obtain accurate execution times,an integrated learning effects model is developed which makes use of experiences.The single virtual machine scheduling problems with the developed learning effects model are proven to be optimally solvable in polynomial time for optimizing makespan,total completion time and the sum of(square)completion times.Those to minimize the total weighted completion time and the maximum lateness are proved to be optimally solvable in polynomial time only for certain assumptions.The developed learning effects model is adapted to two special m-virtual machine flowshop problems.Polynomial-time optimal solutions are provided to them for the same objectives as in the single virtual machine scheduling problems.Optimal solutions are demonstrated by an example for the considered problems using the constructed optimal rules.

关键词： cloud computing virtual machine scheduling task position learning effects

作者: Haiyan Xu Xiaoping Li

作者单位: School of Computer Science and Engineering Southeast University Nanjing,China,211189;Department of P School of Computer Science and Engineering Southeast University Nanjing,China,211189

会议类型: 国内会议

会议名称: 第10届全国计算机支持的协同工作学术会议暨中国计算机学会协同计算专委年度工作会议

会议地点: 太原

会议语种:英文

页码: 411-424

在线出版日期: 2015-08-28（万方平台首次上网日期，不代表论文的发表时间）