• DocumentCode
    1791736
  • Title

    Situation aware computing for big data

  • Author

    Chan, Eric S. ; Gawlick, Dieter ; Ghoneimy, Adel ; Zhen Hua Liu

  • Author_Institution
    Oracle Corp., Redwood Shores, CA, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Big Data applications need a situation aware computing model to manage data, knowledge, and processes in an ever increasing amount, complexity, and speed while reacting as efficiently and timely as possible to any evolving situation. We introduce a Knowledge Intensive Data-processing System (KIDS) that empowers Big Data applications to support situation awareness. Frameworks such as Apache Hadoop YARN can be leveraged for repeated and near real-time execution of knowledge intensive applications. KIDS bridges the gap between the world of low-value data and the world of high-value information and knowledge, which are best handled by state of the art databases. These databases provide a host of much needed functions such as multi-temporality, flashback, provenance, and registered queries. With KIDS model, Big Data applications are well structured and can evolve perpetually.
  • Keywords
    Big Data; distributed processing; query processing; ubiquitous computing; Apache Hadoop YARN; KIDS; big data applications; high-value information; knowledge intensive data-processing system; multitemporality; registered queries; situation aware computing model; Big data; Computational modeling; Context modeling; Data models; Databases; Real-time systems; Yarn; Bi-Temporal; Big Data; Database; Hadoop; Knowledge; Provenance; Situation Awareness; YARN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004415
  • Filename
    7004415