• DocumentCode
    1824385
  • Title

    Using Cloud Technologies to Optimize Data-Intensive Service Applications

  • Author

    Habich, Dirk ; Lehner, Wolfgang ; Richly, Sebastian ; Assmann, Uwe

  • Author_Institution
    Database Technol. Group, Dresden Univ. of Technol., Dresden, Germany
  • fYear
    2010
  • fDate
    5-10 July 2010
  • Firstpage
    19
  • Lastpage
    26
  • Abstract
    The role of data analytics increases in several application domains to cope with the large amount of captured data. Generally, data analytics are data-intensive processes, whose efficient execution is a challenging task. Each process consists of a collection of related structured activities, where huge data sets have to be exchanged between several loosely coupled services. The implementation of such processes in a service-oriented environment offers some advantages, but the efficient realization of data flows is difficult. Therefore, we use this paper to propose a novel SOA-aware approach with a special focus on the data flow. The tight interaction of new cloud technologies with SOA technologies enables us to optimize the execution of data-intensive service applications by reducing the data exchange tasks to a minimum. Fundamentally, our core concept to optimize the data flows is found in data clouds. Moreover, we can exploit our approach to derive efficient process execution strategies regarding different optimization objectives for the data flows.
  • Keywords
    Internet; data analysis; data flow analysis; optimisation; software architecture; cloud technologies; data analytics; data flow; data intensive service applications optimization; service oriented environment; Business; Clouds; Computational modeling; Semantics; Service oriented architecture; Simple object access protocol; data cloud; data-intensive; service applications;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on
  • Conference_Location
    Miami, FL
  • Print_ISBN
    978-1-4244-8207-8
  • Electronic_ISBN
    978-0-7695-4130-3
  • Type

    conf

  • DOI
    10.1109/CLOUD.2010.56
  • Filename
    5558140