• DocumentCode
    2446121
  • Title

    Data Replication and Power Consumption in Data Grids

  • Author

    Vrbsky, Susan V. ; Lei, Ming ; Smith, Karl ; Byrd, Jeff

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Alabama, Tuscaloosa, AL, USA
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 3 2010
  • Firstpage
    288
  • Lastpage
    295
  • Abstract
    While data grids can provide the ability to solve large-scale applications which require the processing of large amounts of data, they have been recognized as extremely energy inefficient. Computing elements can be located far away from the data storage elements. A common solution to improve availability and file access time in such environments is to replicate the data, resulting in the creation of copies of data files at many different sites. The energy efficiency of the data centers storing this data is one of the biggest issues in data intensive computing. Since power is needed to transmit, store and cool the data, we propose to minimize the amount of data transmitted and stored by utilizing smart replication strategies that are data aware. In this paper we present a new data replication approach, called the sliding window replica strategy (SWIN), that is not only data aware, but is also energy efficient. We measure the performance of SWIN and existing replica strategies on our Sage green cluster to study the power consumption of the strategies. Results from this study have implications beyond our cluster to the management of data in clouds.
  • Keywords
    file organisation; grid computing; information retrieval; pattern clustering; SWIN; Sage green cluster; data center; data grid power consumption; data intensive computing; data management; data processing; data replication; data storage element; file access; sliding window replica strategy; Availability; Cooling; Data models; Distributed databases; Energy efficiency; Green products; Servers; data cluster; data grid; data intensive computing; data replication; power consumption; sliding window protocol;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2010 IEEE Second International Conference on
  • Conference_Location
    Indianapolis, IN
  • Print_ISBN
    978-1-4244-9405-7
  • Electronic_ISBN
    978-0-7695-4302-4
  • Type

    conf

  • DOI
    10.1109/CloudCom.2010.35
  • Filename
    5708462