• DocumentCode
    3144848
  • Title

    Energy Efficient Hadoop Using Mirrored Data Block Replication Policy

  • Author

    Yazd, S.A. ; Venkatesan, S. ; Mittal, Natasha

  • Author_Institution
    Sch. of Eng. & Comput. Sci., Univ. of Texas at Dallas, Richardson, TX, USA
  • fYear
    2012
  • fDate
    8-11 Oct. 2012
  • Firstpage
    457
  • Lastpage
    462
  • Abstract
    MapReduce scheme has became the state of the art in parallel processing of vast amount of data in distributed systems. Hadoop, as a popular open-source implementation of this technique, makes use of data block replication mechanism to provide a reliable and fault-tolerant design. To maintain data availability, Hadoop takes into account the possibilities of node and rack failures. Hence, it stores multiple copies of each data block to ensure availability and reliability. The current data block placement policy is to randomly distribute the replicas on all servers, satisfying some constraints such as preventing storage of two replicas of a data block on a single node. Our study proposes an efficient placement policy for data block replicas, which can reduce the consumed energy in data centers. The proposed policy is built upon the covering subset (CovSet) method. The effectiveness of the proposed approach is confirmed through simulations. Also, our experiments show that the proposed method becomes more effective whenever the average number of data blocks per server increases, which corresponds to the actual conditions in practice.
  • Keywords
    computer centres; energy conservation; energy consumption; fault tolerant computing; parallel processing; power aware computing; public domain software; system recovery; CovSet method; MapReduce scheme; covering subset method; data availability; data block placement policy; data block replicas; data block replication mechanism; datacenter energy consumption; distributed systems; energy efficient Hadoop; fault-tolerant design; mirrored data block replication policy; open-source implementation; parallel processing; rack failures; reliable design; server replicas; Availability; Data models; Distributed databases; Measurement; Peer to peer computing; Servers; Hadoop; data block replication; energy efficiency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliable Distributed Systems (SRDS), 2012 IEEE 31st Symposium on
  • Conference_Location
    Irvine, CA
  • ISSN
    1060-9857
  • Print_ISBN
    978-1-4673-2397-0
  • Type

    conf

  • DOI
    10.1109/SRDS.2012.25
  • Filename
    6424895