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
  • [21] Temperature and energy-aware consolidation algorithms in cloud computing
    Maede Yavari
    Akbar Ghaffarpour Rahbar
    Mohammad Hadi Fathi
    Journal of Cloud Computing, 8
  • [22] Optimizing Power and Energy Efficiency in Cloud Computing
    Khan, Naveed
    Haugerud, Harek
    Shrestha, Raju
    Yazidi, Anis
    11TH INTERNATIONAL CONFERENCE ON MANAGEMENT OF DIGITAL ECOSYSTEMS (MEDES), 2019, : 256 - 261
  • [23] Energy efficiency in Mobile Cloud Computing Architectures
    Thinh Le Vinh
    Pallavali, Reddy
    Houacine, Fatiha
    Bouzefrane, Samia
    2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW), 2016, : 326 - 331
  • [24] Green Cloud? An Empirical Analysis of Cloud Computing and Energy Efficiency
    Park, Jiyong
    Han, Kunsoo
    Lee, Byungtae
    MANAGEMENT SCIENCE, 2023, 69 (03) : 1639 - 1664
  • [25] Smartphone Based Computing Cloud and Energy Efficiency
    Mamchych, Olexander
    Volk, Maksym
    2022 12TH INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS, SERVICES AND TECHNOLOGIES (DESSERT), 2022,
  • [26] Using Ant Colony System to Consolidate VMs for Green Cloud Computing
    Farahnakian, Fahimeh
    Ashraf, Adnan
    Pahikkala, Tapio
    Liljeberg, Pasi
    Plosila, Juha
    Porres, Ivan
    Tenhunen, Hannu
    IEEE TRANSACTIONS ON SERVICES COMPUTING, 2015, 8 (02) : 187 - 198
  • [27] An Efficient Resource Utilization Technique for Consolidation of Virtual Machines in Cloud Computing Environments
    Selim, Gamal Eldin I.
    El-Rashidy, Mohamed A.
    El-Fishawy, Nawal A.
    2016 33RD NATIONAL RADIO SCIENCE CONFERENCE (NRSC), 2016, : 316 - 324
  • [28] Load Balancing and Server Consolidation in Cloud Computing Environments: A Meta-Study
    Ala'anzy, Mohammed
    Othman, Mohamed
    IEEE ACCESS, 2019, 7 : 141868 - 141887
  • [29] A Stochastic Modeling for VM Consolidation in Cloud Computing
    Park, Minho
    Yun, Ji-Hoon
    Nam, Seung Yeob
    JOURNAL OF INTERNET TECHNOLOGY, 2014, 15 (06): : 1051 - 1058
  • [30] Energy-Aware Profiling for Cloud Computing Environments
    Alzamil, Ibrahim
    Djemame, Karim
    Armstrong, Django
    Kavanagh, Richard
    ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE, 2015, 318 : 91 - 108