A Simulated Annealing Combined Genetic Algorithm for Virtual Machine Migration in Cloud Datacenters

被引:6
作者
Li, Yidong [1 ]
Meng, Xiangjun [2 ]
Dong, Hairong [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China
[2] State Grid Shandong Power Co, Jinan, Peoples R China
[3] State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
来源
2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC | 2016年
关键词
cloud computing; resource allocation; virtual machine migration; simulated annealing; genetic algorithm; CONSOLIDATION;
D O I
10.1109/DASC-PICom-DataCom-CyberSciTec.2016.108
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Resource allocation in data centers is a significant research area in cloud computing. A high-efficiency resource allocation strategy can save the operating cost for cloud service providers, and less amount of carbon dioxide emissions to the atmosphere. While the Service Level Agreement(SLA) of customers can be guaranteed. So the cloud providers have to deal with the cost-performance trade-off: the minimization of cost, while meeting the SLAs. In this paper, we present a simulated annealing combined genetic algorithm based virtual machine migration strategy for solving the resource allocation and scheduling problem in cloud computing environment, which models the resource allocation as a binary multiple knapsack problem. Experimental results show that this method is able to achieve better data center operation cost then basic genetic algorithms.
引用
收藏
页码:572 / 577
页数:6
相关论文
共 28 条
  • [1] [Anonymous], 2007, P 2 INT WORKSH VIRT
  • [2] Arzuaga E., 2010, P 1 JOINT WOSP SIPEW, P235
  • [3] Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers
    Beloglazov, Anton
    Buyya, Rajkumar
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2012, 24 (13) : 1397 - 1420
  • [4] Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing
    Beloglazov, Anton
    Abawajy, Jemal
    Buyya, Rajkumar
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (05): : 755 - 768
  • [5] Ants and multiple knapsack problem
    Boryczka, Urszula
    [J]. 6TH INTERNATIONAL CONFERENCE ON COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT APPLICATIONS, PROCEEDINGS, 2007, : 149 - +
  • [6] CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
    Calheiros, Rodrigo N.
    Ranjan, Rajiv
    Beloglazov, Anton
    De Rose, Cesar A. F.
    Buyya, Rajkumar
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2011, 41 (01) : 23 - 50
  • [7] Dynamic VM consolidation for energy-aware and SLA violation reduction in cloud computing
    Cao, Zhibo
    Dong, Shoubin
    [J]. 2012 13TH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED COMPUTING, APPLICATIONS, AND TECHNOLOGIES (PDCAT 2012), 2012, : 363 - 369
  • [8] Choi HW, 2008, ICS'08: PROCEEDINGS OF THE 2008 ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, P185
  • [9] A genetic algorithm for the multidimensional knapsack problem
    Chu, PC
    Beasley, JE
    [J]. JOURNAL OF HEURISTICS, 1998, 4 (01) : 63 - 86
  • [10] Clark C, 2005, USENIX ASSOCIATION PROCEEDINGS OF THE 2ND SYMPOSIUM ON NETWORKED SYSTEMS DESIGN & IMPLEMENTATION (NSDI '05), P273