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
  • [41] An evergreen cloud: Optimizing energy efficiency in heterogeneous cloud computing architectures
    Abu Sharkh, Mohamed
    Shami, Abdallah
    VEHICULAR COMMUNICATIONS, 2017, 9 : 199 - 210
  • [42] Emerging models to improve storage management techniques in cloud computing environments
    Caragnano, Giuseppe
    Mossucca, Lorenzo
    2015 9TH INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS CISIS 2015, 2015, : 200 - 203
  • [43] An Efficient Energy Saving Task Consolidation Algorithm for Cloud Computing Systems
    Panda, Sanjaya K.
    Jana, Prasanta K.
    2014 INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING (PDGC), 2014, : 262 - 267
  • [44] Modeling and Managing Energy Efficiency Data Center by a Live Migration Mechanism in Mobile Cloud Computing Environments
    Sun, Dawei
    Chang, Guiran
    Wang, Dongqi
    Chen, Dong
    Wang, Xingwei
    SENSOR LETTERS, 2012, 10 (08) : 1855 - 1861
  • [45] A survey on techniques to achive energy efficiency in cloud computing
    Singh, Sobinder
    Kumar, Ajay
    Swaroop, Abhishek
    Anamika
    2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA), 2016, : 1281 - 1285
  • [46] An Efficient Task Consolidation Algorithm for Cloud Computing Systems
    Panda, Sanjaya K.
    Jana, Prasanta K.
    DISTRIBUTED COMPUTING AND INTERNET TECHNOLOGY (ICDCIT 2016), 2016, 9581 : 61 - 74
  • [47] Hierarchical Virtual Machine Consolidation in a Cloud Computing System
    Hwang, Inkwon
    Pedram, Massoud
    2013 IEEE SIXTH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD 2013), 2013, : 196 - 203
  • [48] Structure-aware online virtual machine consolidation for datacenter energy improvement in cloud computing
    Esfandiarpoor, Sina
    Pahlavan, Ali
    Goudarzi, Maziar
    COMPUTERS & ELECTRICAL ENGINEERING, 2015, 42 : 74 - 89
  • [49] Energy Efficiency Techniques in Cloud Computing: A Survey and Taxonomy
    Kaur, Tarandeep
    Chana, Inderveer
    ACM COMPUTING SURVEYS, 2015, 48 (02)
  • [50] Online VM Consolidation in Cloud Environments
    Alsadie, Deafallah
    Tari, Zahir
    Alzahrani, Eidah J.
    2019 IEEE 12TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (IEEE CLOUD 2019), 2019, : 137 - 145