• DocumentCode
    3587596
  • Title

    Analysis on enhancing storm to efficiently process big data in real time

  • Author

    Nivash, J.P. ; Deni Raj, Ebin ; Dhinesh Babu, L.D. ; Nirmala, M. ; Manoj, Kumar V.

  • Author_Institution
    Sch. of Inf. Technol. & Eng., VIT Univ., Vellore, India
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The rapid growth of huge data has become a challenge to the data analysts in recent time. As the data is growing exponentially many techniques are on the rise, for processing the real time data. Many data processing models like Hadoop, Apache YARN, Mapreduce, Storm, and Akka are leading the Big Data domain. This paper analyses and compares all the data processing models stated above. Researchers are trying to increase the efficiency of the algorithms used in the data processing. In this paper, we propose two algorithms namely JATS and SD, which will enhance the efficiency of the storm data processing architecture.
  • Keywords
    Big Data; data analysis; distributed processing; Akka; Apache YARN; Big data domain; Hadoop; JATS; Mapreduce; SD; Storm data processing architecture; data analysts; data processing models; Algorithm design and analysis; Data models; Data processing; Fasteners; Real-time systems; Storms; Topology; Apache Storm; Bigdata; Hadoop; Real time data processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on
  • Print_ISBN
    978-1-4799-2695-4
  • Type

    conf

  • DOI
    10.1109/ICCCNT.2014.7093076
  • Filename
    7093076