基于萤火虫算法的虚拟机部署能效优化策略
|
摘要
综合考虑数据中心能耗、应用SLA违例及虚拟机迁移量的均衡优化,提出一种基于萤火虫算法的虚拟机部署优化策略。建立虚拟机部署优化的目标函数与约束条件,利用装箱思想对虚拟机部署进行抽象,设计基于萤火虫算法的虚拟机部署优化方法,通过萤火虫种群初始化、萤光素更新、萤火虫移动以及局部半径范围更新4个阶段的最优解搜索过程,实现虚拟机部署能效优化。实验结果表明,该算法可以通过虚拟机重部署实现数据中心能耗与性能的均衡优化。
For considering synthetically the trade-off optimization of the energy consumption in data center,SLA violation of applications and the number of virtual machine migration,a virtual machine placement optimization strategy based on glowworm swarm optimization algorithm was presented.The objective function and the corresponding constraints of the virtual machine placement were established.The bin-packing idea was used to abstract the virtual machine placement problem.A virtual machine placement optimization method based on glowworm swarm optimization algorithm was designed.A four-stage optimal searching process was used,including the population initialization of glowworm swarm,updating the luciferin,the movement of glowworm and updating the local radius range,to complete the optimal virtual machine placement.Experimental results show that the proposed algorithm can trade-off the energy consumption of data center and the performance of applications by the re-placement of virtual machines.
For considering synthetically the trade-off optimization of the energy consumption in data center,SLA violation of applications and the number of virtual machine migration,a virtual machine placement optimization strategy based on glowworm swarm optimization algorithm was presented.The objective function and the corresponding constraints of the virtual machine placement were established.The bin-packing idea was used to abstract the virtual machine placement problem.A virtual machine placement optimization method based on glowworm swarm optimization algorithm was designed.A four-stage optimal searching process was used,including the population initialization of glowworm swarm,updating the luciferin,the movement of glowworm and updating the local radius range,to complete the optimal virtual machine placement.Experimental results show that the proposed algorithm can trade-off the energy consumption of data center and the performance of applications by the re-placement of virtual machines.
引文
[1]JING Chao,CHENG Xiaohui.Research of virtual machine placement algorithm for latency optimizaiton on cloud data center[J].Application Research of Computers,2017,34(12):3792-3796(in Chinese).[敬超,程小辉.面向云数据中心的虚拟机部署时延优化算法研究[J].计算机应用研究,2017,34(12):3792-3796.]
[2]Beloglazov A,Buyya R.Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers[J].Concurrency&Computation Practice&Experience,2013,24(13):1397-1420.
[3]Kaaouache MA,Bouamama S.Solving bin packing problem with a hybrid genetic algorithm for VM placement in cloud[J].Procedia Computer Science,2015,60(1):1061-1069.
[4]Wu Y,Tang M,Fraser W.A simulated annealing algorithm for energy efficient virtual machine placement[C]//IEEE International Conference on Systems,Man,and Cybernetics,2012:1245-1250.
[5]Wang S,Liu Z,Zheng Z,et al.Particle swarm optimization for energy-aware virtual machine placement optimization in virtualized data centers[C]//International Conference on Parallel and Distributed Systems,2014:102-109.
[6]Feller E,Rilling L,Morin C.Energy-aware ant colony based workload placement in clouds[C]//IEEE/ACM International Conference on Grid Computing,2013:26-33.
[7]Liu XF,Zhan ZH,Du KJ,et al.Energy aware virtual machine placement scheduling in cloud computing based on ant colony optimization approach[C]//Conference on Genetic and Evolutionary Computation.ACM,2014:41-48.
[8]Xiong AP,Xu CX.Energy efficient multiresource allocation of virtual machine based on PSO in cloud data center[J].Mathematical Problems in Engineering,2014(5):1-8.
[9]Khalilzad N,Faragardi HR,Nolte T.Towards energy-aware placement of real-time virtual machines in a cloud data center[C]//International Conference on High Performance Computing and Communications,IEEE Computer Society,2015:1657-1662.
[10]Sharma K,Reddy M.Novel energy efficient virtual machine allocation at data center using genetic algorithm[C]//International Conference on Signal Processing,Communication and Networking.IEEE,2015:1-6.
[11]Liu C,Shen C,Li S,et al.A new evolutionary multi-objective algorithm to virtual machine placement in virtualized data center[C]//IEEE International Conference on Software Engineering and Service Science,2014:272-275.
[12]Jamali S,Malektaji S.Improving grouping genetic algorithm for virtual machine placement in cloud data centers[C]//International Conference on Computer and Knowledge Engineering.IEEE,2014:328-333.
[13]Joseph CT,Chandrasekaran K,Cyriac R.Improving the efficiency of genetic algorithm approach to virtual machine allocation[C]//International Conference on Computer and Communication Technology.IEEE,2015:111-116.
[14]Ferdaus MH,Murshed M,Calheiros RN,et al.Virtual machine consolidation in cloud data centers using ACO metaheuristic[C]//European Conference on Parallel Processing.Springer International Publishing,2014:306-317.
[15]Tawfeek MA,El-Sisi AB,Keshk AE,et al.Virtual machine placement based on ant colony optimization for minimizing resource wastage[C]//International Conference on Advanced Machine Learning Technologies and Applications.Springer International Publishing,2014:153-164.
[16]Pires FL,Baran B.Multi-objective virtual machine placement with service level agreement:A memetic algorithm approach[C]//IEEE/ACM International Conference on Utility&Cloud Computing.IEEE,2014.
[2]Beloglazov A,Buyya R.Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers[J].Concurrency&Computation Practice&Experience,2013,24(13):1397-1420.
[3]Kaaouache MA,Bouamama S.Solving bin packing problem with a hybrid genetic algorithm for VM placement in cloud[J].Procedia Computer Science,2015,60(1):1061-1069.
[4]Wu Y,Tang M,Fraser W.A simulated annealing algorithm for energy efficient virtual machine placement[C]//IEEE International Conference on Systems,Man,and Cybernetics,2012:1245-1250.
[5]Wang S,Liu Z,Zheng Z,et al.Particle swarm optimization for energy-aware virtual machine placement optimization in virtualized data centers[C]//International Conference on Parallel and Distributed Systems,2014:102-109.
[6]Feller E,Rilling L,Morin C.Energy-aware ant colony based workload placement in clouds[C]//IEEE/ACM International Conference on Grid Computing,2013:26-33.
[7]Liu XF,Zhan ZH,Du KJ,et al.Energy aware virtual machine placement scheduling in cloud computing based on ant colony optimization approach[C]//Conference on Genetic and Evolutionary Computation.ACM,2014:41-48.
[8]Xiong AP,Xu CX.Energy efficient multiresource allocation of virtual machine based on PSO in cloud data center[J].Mathematical Problems in Engineering,2014(5):1-8.
[9]Khalilzad N,Faragardi HR,Nolte T.Towards energy-aware placement of real-time virtual machines in a cloud data center[C]//International Conference on High Performance Computing and Communications,IEEE Computer Society,2015:1657-1662.
[10]Sharma K,Reddy M.Novel energy efficient virtual machine allocation at data center using genetic algorithm[C]//International Conference on Signal Processing,Communication and Networking.IEEE,2015:1-6.
[11]Liu C,Shen C,Li S,et al.A new evolutionary multi-objective algorithm to virtual machine placement in virtualized data center[C]//IEEE International Conference on Software Engineering and Service Science,2014:272-275.
[12]Jamali S,Malektaji S.Improving grouping genetic algorithm for virtual machine placement in cloud data centers[C]//International Conference on Computer and Knowledge Engineering.IEEE,2014:328-333.
[13]Joseph CT,Chandrasekaran K,Cyriac R.Improving the efficiency of genetic algorithm approach to virtual machine allocation[C]//International Conference on Computer and Communication Technology.IEEE,2015:111-116.
[14]Ferdaus MH,Murshed M,Calheiros RN,et al.Virtual machine consolidation in cloud data centers using ACO metaheuristic[C]//European Conference on Parallel Processing.Springer International Publishing,2014:306-317.
[15]Tawfeek MA,El-Sisi AB,Keshk AE,et al.Virtual machine placement based on ant colony optimization for minimizing resource wastage[C]//International Conference on Advanced Machine Learning Technologies and Applications.Springer International Publishing,2014:153-164.
[16]Pires FL,Baran B.Multi-objective virtual machine placement with service level agreement:A memetic algorithm approach[C]//IEEE/ACM International Conference on Utility&Cloud Computing.IEEE,2014.