面向移动云计算的自适应虚拟机调度算法

Self-adaptive Virtual Machine Scheduling Algorithm for Mobile Cloud Computing

随着移动云计算的快速发展和应用普及,如何对移动云中心资源进行有效管理同时又降低能耗、确保资源高可用是目前移动云计算数据中心的热点问题之一.本文从CPU、内存、网络带宽和磁盘四个维度,建立了基于多目标优化的虚拟机调度模型VMSM-EUN(Virtual Machine Scheduling Model based on Energy consumption,Utility and minimum Number of servers),将最小化数据中心能耗、最大化数据中心效用以及最小化服务器数量作为调度目标.设计了基于改进粒子群的自适应参数调整的虚拟机调度算法VMSA-IPSO(Virtual Machine Scheduling Algorithm based on Improved Particle Swarm Optimization)来求解该模型.最后通过仿真实验验证了本文提出的调度算法的可行性与有效性.对比实验结果表明,本文设计的基于改进粒子群的自适应虚拟机调度算法在进行虚拟机调度时,能在降低能耗的同时提高数据中心效用.

With the rapid development of mobile cloud computing and the popularity of applications,How to effectively manage mobile cloud center resources while reducing energy consumption and ensuring high resource availability is one of the hot issues in mobile cloud computing data centers.In this paper,focusing on four dimensions of CPU,memory,network bandwidth,and disk,we establish a virtual machine scheduling model VMSM-EUN based on multi-objective optimization which can minimize the data center energy consumption,maximize data center utility,and minimize the number of servers.We propose a virtual machine scheduling algorithm VMSA-IPSO based on improved particle swarm optimization to solve the model.The improvement includes adaptive parameter adjustment.Finally,the effectiveness of the proposed algorithm is verified by simulation experiments.The experimental results show that the adaptive virtual machine scheduling algorithm can improve the efficiency of data center while reducing energy consumption.