• DocumentCode
    1665540
  • Title

    CEPSim: A Simulator for Cloud-Based Complex Event Processing

  • Author

    Higashino, Wilson A. ; Capretz, Miriam A. M. ; Bittencourt, Luiz F.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Western Univ., London, ON, Canada
  • fYear
    2015
  • Firstpage
    182
  • Lastpage
    190
  • Abstract
    As one of the Vs defining Big Data, data velocity brings many new challenges to traditional data processing approaches. The adoption of cloud environments in complex event processing (CEP) systems is a recent architectural style that aims to overcome these challenges. Validating cloud-based CEP systems at the required Big Data scale, however, is often a laborious, error-prone, and expensive task. This article presents CEPSim, a new simulator that has been developed to facilitate this validation process. CEPSim extends CloudSim, an existing cloud simulator, with an application model based on directed acyclic graphs that is used to represent continuous CEP queries. Once defined, the queries can be simulated in different cloud environments under diverse load conditions. Moreover, CEPSim is also customizable with different operator placement and scheduling strategies. These features enable researchers and system architects to experiment with different configurations and strategies and to promote research in this field. Experimental results show that CEPSim can successfully simulate existing cloud-based CEP systems.
  • Keywords
    Big Data; cloud computing; directed graphs; Big Data; CEP queries; CEPSim; CloudSim; application model; cloud environments; cloud simulator; cloud-based CEP systems; cloud-based complex event processing; data processing; data velocity; directed acyclic graphs; load conditions; operator placement; scheduling strategies; validation process; Big data; Cloud computing; Computational modeling; Digital signal processing; Generators; Terminology; Virtual machining; Big Data; cloud computing; complex event processing; simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2015 IEEE International Congress on
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-7277-0
  • Type

    conf

  • DOI
    10.1109/BigDataCongress.2015.34
  • Filename
    7207218