一种云计算资源的多目标优化的调度方法
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摘要
云计算通过虚拟化技术将基础设施硬件资源虚拟化,以动态可缩放的方式提供给用户。云计算基础设施规模不断增加导致资源调度系统负载不均衡,从而造成资源浪费等问题。提出多目标优化资源调度策略和相应的算法,试图同时满足多个资源调度优化目标,如减少资源浪费,降低服务等级约定(SLA)违背率、保持系统负载均衡等。通过仿真实验,验证了多目标优化资源调度的策略能够在多个相互冲突的目标之间实现最优权衡。
Cloud computing infrastructure virtualizes hardware resource by virtualization technology, and provides it to users in scalable way. The increasing size of cloud computing infrastructure results in the waste of resources because of system load imbalance and other issues. This paper proposes a multi-objective optimization of resource scheduling policies and a related algorithm that can simultaneously achieve multiple objectives, such as reducing the waste of resources, reducing the service level agreement(SLA) and keep the system load balance. Simulation results show that the multi-objective optimization of resource scheduling method can achieve the optimal trade-offs among multiple conflicting goals.
Cloud computing infrastructure virtualizes hardware resource by virtualization technology, and provides it to users in scalable way. The increasing size of cloud computing infrastructure results in the waste of resources because of system load imbalance and other issues. This paper proposes a multi-objective optimization of resource scheduling policies and a related algorithm that can simultaneously achieve multiple objectives, such as reducing the waste of resources, reducing the service level agreement(SLA) and keep the system load balance. Simulation results show that the multi-objective optimization of resource scheduling method can achieve the optimal trade-offs among multiple conflicting goals.
引文
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[2]UHLIG R,NEIGER G,RODGERS D,et al.Intel virtualization technology[J].Computer,2005,38(5):48-56.
[3]CHEN Y,DAS A,QIN W,et al.Managing server energy and operational costs in hosting centers[C].ACM SIGMETRICS Performance Evaluation Review,ACM,2005,33(1):303-314.
[4]KUSIC D,KEPHART J O,HANSON J E,et al.Power and performance management of virtualized computing environments via lookaheadcontrol[J].Cluster Computing,2009,12(1):1-15.
[5]HU J,GU J,SUN G,et al.A scheduling strategy on load balancing of virtual machine resources in cloud computing environment[C].Parallel Architectures,Algorithms and Programming(PAAP),2010 Third International Symposium on.IEEE,2010:89-96.
[6]WOOD T,SHENOY P J,VENKATARAMANI A,et al.Black-box and Gray-box strategies for virtual machine migration[C].NSDI,2007:17-17.
[7]TANG C,STEINDER M,SPREITZER M,et al.A scalable application placement controller for enterprise data centers[C].Proceedings of the 16th International Conference on World Wide Web,ACM,2007:331-340.
[8]BOX G E P,JENKINS G M,REINSEL G C.Time series analysis:forecasting and control[M].New York:John Wiley&Sons,2013.
[9]CALHEIROS R N,RANJAN R,BELOGLAZOV A,et al.Cloud Sim:a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms[J].Software:Practice and Experience,2011,41(1):23-50.