Consolidation of VMs to improve energy efficiency in cloud computing environments

被引:11
作者
Okada, Thiago Kenji [1 ]
Vigliotti, Albert De la Fuente [1 ]
Batista, Daniel Macedo [1 ]
Vel Lejbman, Alfredo Goldman [1 ]
机构
[1] Univ Sao Paulo, Inst Math & Stat IME, Sao Paulo, Brazil
来源
2015 XXXIII BRAZILIAN SYMPOSIUM ON COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS | 2015年
关键词
cloud computing; green computing; virtual machine; scheduling;
D O I
10.1109/SBRC.2015.27
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Improvement of energy efficiency in IT is an important research topic nowadays. The reduction of operational costs, generated heat and environment impact are some of the reasons for this. Thanks to the advent of cloud computing, it is possible to improve energy efficiency in data centers by running various virtual machines in a single physical machine. However, the cloud providers generally invest in performance, not energy efficiency. This paper focuses on the problem of an energy efficient initial VM placement, and describes three new algorithms for this problem, one based on the First Fit Decreasing algorithm, and the other two based on the Best Fit Decreasing algorithm. They are compared with other algorithms in the literature, and a reduction of power consumption up to 3.24% was observed, as well a reduction of execution time in several orders of magnitude. Scripts used to analyze traces publicly provided by Google are another contribution of the paper, since they are useful for those working in mechanisms for cloud computing.
引用
收藏
页码:150 / 158
页数:9
相关论文
共 50 条
  • [1] Dynamic VMs placement for energy efficiency by PSO in cloud computing
    Dashti, Seyed Ebrahim
    Rahmani, Amir Masoud
    JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2016, 28 (1-2) : 97 - 112
  • [2] CloudESE: Energy Efficiency Model for Cloud Computing Environments
    Sarji, Imad
    Ghali, Cesar
    Chehab, Ali
    Kayssi, Ayman
    2011 INTERNATIONAL CONFERENCE ON ENERGY AWARE COMPUTING, 2011,
  • [3] CloudESE: Energy efficiency model for cloud computing environments
    Sarji I.
    Ghali C.
    Chehab A.
    Kayssi A.
    2011 International Conference on Energy Aware Computing, ICEAC 2011, 2011,
  • [4] Mapping and Consolidation of VMs Using Locust-Inspired Algorithms for Green Cloud Computing
    Mohammed Alaa Ala’anzy
    Mohamed Othman
    Neural Processing Letters, 2022, 54 : 405 - 421
  • [5] Toward Secure VMs Allocation: Analysis of VMs Allocation Behaviours in the Cloud Computing Environments
    Aldawood, Mansour
    Jhumka, Arshad
    Fahmy, Suhaib A.
    CLOUD COMPUTING AND SERVICES SCIENCE, CLOSER 2021, 2022, 1607 : 25 - 46
  • [6] Mapping and Consolidation of VMs Using Locust-Inspired Algorithms for Green Cloud Computing
    Ala'anzy, Mohammed Alaa
    Othman, Mohamed
    NEURAL PROCESSING LETTERS, 2022, 54 (01) : 405 - 421
  • [7] Energy-Efficiency in Cloud Computing Environments: Towards Energy Savings without Performance Degradation
    Moreno, Ismael Solis
    Xu, Jie
    INTERNATIONAL JOURNAL OF CLOUD APPLICATIONS AND COMPUTING, 2011, 1 (01) : 17 - 33
  • [8] Energy Efficiency in Cloud Computing and Distributed Systems
    Barbulescu, Mihai
    Grigoriu, Ramona-Oana
    Neculoiu, Giorgian
    Halcu, Ionela
    Sandulescu, Virginia Cristiana
    Niculescu-Faida, Oana
    Marinescu, Mariana
    Marinescu, Viorel
    2013 ROEDUNET INTERNATIONAL CONFERENCE: NETWORKING IN EDUCATION AND RESEARCH, 12TH EDITION, 2013,
  • [9] Optimizing Power and Energy Efficiency in Cloud Computing
    Khan, Naveed
    Shrestha, Raju
    CLOSER: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE, 2019, : 380 - 387
  • [10] Energy and cost-aware virtual machine consolidation in cloud computing
    Yousefipour, Amin
    Rahmani, Amir Masoud
    Jahanshahi, Mohsen
    SOFTWARE-PRACTICE & EXPERIENCE, 2018, 48 (10) : 1758 - 1774