• DocumentCode
    267100
  • Title

    Energy Efficiency Dilemma: P2P-cloud vs. Datacenter

  • Author

    Sharifi, Leila ; Rameshan, Navaneeth ; Freitag, Felix ; Veiga, Luis

  • Author_Institution
    Tecnico Lisboa/INESC-ID Lisboa, Lisbon, Portugal
  • fYear
    2014
  • fDate
    15-18 Dec. 2014
  • Firstpage
    611
  • Lastpage
    619
  • Abstract
    Energy consumption is increasing in the IT sector and a remarkable part of this energy is consumed in data centers. Numerous techniques have been proposed to solve the energy efficiency issue in cloud systems. Recently, there are some efforts to decentralize the cloud via distributing data centers in diverse geographical positions. In this paper, we elaborate on the energy consumption of different cloud architectures, from a mega-datacenter to a P2P-cloud that provides extreme decentralization in terms of datacenter size. P2P-cloud is defined as a set of commodity host machines, connected to each other to serve a community. Our evaluation results reveal the fact that the more decentralized the system is, the less energy may be consumed in the system. Studying the energy efficiency of P2P-cloud infrastructure shows that the additional system design complexity involved is warranted with improved energy-efficiency and better locality for some services. Our analysis indicates that such P2P-cloud outperforms the classic datacenter model as long as it meets the locality conditions, which are commonplace in communities. Moreover, we illustrate how much energy can be saved for MapReduce applications with a diverse range of specifications by switching to P2P-cloud.
  • Keywords
    cloud computing; computer centres; energy conservation; energy consumption; parallel processing; peer-to-peer computing; IT sector; MapReduce applications; P2P-cloud; cloud architectures; commodity host machines; datacenter size; energy consumption; energy efficiency dilemma; locality conditions; mega-datacenter; system design complexity; Cloud computing; Communities; Cooling; Energy consumption; Power demand; Wireless communication; Energy efficiency; MapReduce; P2P-cloud; datacenter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/CloudCom.2014.137
  • Filename
    7037724