Virtual Machine Placement. A Multi-Objective Approach

被引:0
|
作者
Pires, Fabio Lopez [1 ]
Melgarejo, Elias [2 ]
Baran, Benjamin [3 ,4 ]
机构
[1] Parque Tecnol Itaipu, Ctr Datos, Hernandarias, Paraguay
[2] Univ Nacil Este, Fac Politecn, Ciudad del Este, Spain
[3] Univ Nacil Este, Ciudad del Este, Spain
[4] Univ Nacl Asunc, San Lorenzo, Paraguay
关键词
Virtualization; Resources Allocation; Datacenter; Cloud Computing; Energy Efficiency; Multi-Objective Optimization;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The process of selecting which virtual machines will be placed (i.e. executed) in the physical machines available in a Datacenter is known as virtual machine placement problem. This work proposes for the first time a formulation of the problem, with a multi-objective approach, of the main objective functions studied so far as mono-objective in the state of the art. Also it is proposed a multi-objective memetic algorithm for solving the proposed problem. The validity of the proposed formulation is checked by comparing experimental results of the proposed algorithm with a brute force algorithm. Finally it is experimentally verified the scalability of the used meta-heuristic.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Multi-objective Virtual Machine Placement for Load Balancing
    Fang, Feng
    Qu, Bin-Bin
    [J]. 2017 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (IST 2017), 2017, 11
  • [2] Multi-objective optimization for rebalancing virtual machine placement
    Li, Rui
    Zheng, Qinghua
    Li, Xiuqi
    Yan, Zheng
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2020, 105 : 824 - 842
  • [3] Virtual Machine Placement Strategy Based on Multi-objective Optimization
    Liu, Jun
    Dai, Fu-Cheng
    Xin, Ning
    [J]. Dongbei Daxue Xuebao/Journal of Northeastern University, 2022, 43 (05): : 609 - 617
  • [4] Virtual machine placement based on multi-objective reinforcement learning
    Yao Qin
    Hua Wang
    Shanwen Yi
    Xiaole Li
    Linbo Zhai
    [J]. Applied Intelligence, 2020, 50 : 2370 - 2383
  • [5] Virtual machine placement based on multi-objective reinforcement learning
    Qin, Yao
    Wang, Hua
    Yi, Shanwen
    Li, Xiaole
    Zhai, Linbo
    [J]. APPLIED INTELLIGENCE, 2020, 50 (08) : 2370 - 2383
  • [6] Multi-Objective Virtual Machine Placement Optimization for Cloud Computing
    Dorterler, Serap
    Dorterler, Murat
    Ozdemir, Suat
    [J]. 2017 INTERNATIONAL SYMPOSIUM ON NETWORKS, COMPUTERS AND COMMUNICATIONS (ISNCC), 2017,
  • [7] A Multi-Objective Biogeography-Based Optimization for Virtual Machine Placement
    Zheng, Qinghua
    Li, Rui
    Li, Xiuqi
    Wu, Jie
    [J]. 2015 15TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING, 2015, : 687 - 696
  • [8] A Novel Multi-Objective Optimization Scheme for Rebalancing Virtual Machine Placement
    Li, Rui
    Zheng, Qinghua
    Li, Xiuqi
    Wu, Jie
    [J]. PROCEEDINGS OF 2016 IEEE 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), 2016, : 710 - 717
  • [9] Dynamic Multi-Objective Virtual Machine Placement in Cloud Data Centers
    Prodan, Radu
    Torre, Ennio
    Durillo, Juan J.
    Aujla, Gagangeet Singh
    Kummar, Neeraj
    Fard, Hamid Mohammadi
    Benedikt, Shajulin
    [J]. 2019 45TH EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA 2019), 2019, : 92 - 99
  • [10] Multi-objective ACO Virtual Machine Placement in Cloud Computing Environments
    Malekloo, Mohammadhossein
    Kara, Nadjia
    [J]. 2014 GLOBECOM WORKSHOPS (GC WKSHPS), 2014, : 112 - 116