• DocumentCode
    2027681
  • Title

    Tutorial: Elastic and Fault Tolerant Event Stream Processing using StreamMine3G

  • Author

    Martin, Andrew ; Le Quoc, Do

  • Author_Institution
    Tech. Univ. Dresden, Dresden, Germany
  • fYear
    2013
  • fDate
    9-12 Dec. 2013
  • Abstract
    The massive amount of new data being generated each day by data sources such as smartphones and sensor devices calls for new techniques to process such continues streams of data. Event Stream Processing (ESP) addresses this problem and enables users to process such data streams in (soft) realtime allowing the detection as well as a quick reaction to relevant situations. In this tutorial, we will introduce the participants to ESP techniques as well as ESP systems such as Storm, Apache S4 and StreamMine3G. We will cover aspects such as programming models, fault tolerance as well as elasticity and cloud support of these platforms.
  • Keywords
    cloud computing; data mining; fault tolerant computing; Apache S4; ESP; Storm; StreamMine3G; cloud support; elasticity; fault tolerance; fault tolerant event stream processing; programming models; sensor devices; smartphones; Cloud computing; Data processing; Elasticity; Fault tolerance; Fault tolerant systems; Tutorials; cep; deterministic execution; elasticity; esp; event stream processing; fault tolerance; mapreduce;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Utility and Cloud Computing (UCC), 2013 IEEE/ACM 6th International Conference on
  • Conference_Location
    Dresden
  • Type

    conf

  • DOI
    10.1109/UCC.2013.18
  • Filename
    6809332