• DocumentCode
    1887275
  • Title

    Approximate matching in publish/ subscribe

  • Author

    Liu, Haifeng ; Jacobsen, Hans-Arno

  • Author_Institution
    Dept. of Comput. Sci., Toronto Univ., Ont., Canada
  • Volume
    1
  • fYear
    2003
  • fDate
    16-20 July 2003
  • Firstpage
    192
  • Abstract
    The publish/subscribe paradigm has found wide-spread applications, including selective information dissemination, location-based services, enterprises application integration, and network management. However, all existing publish/subscribe system models cannot capture any kind of uncertainty naturally inherent to many real world scenarios about formulated. To address this shortcoming, this paper proposes a new publish/subscribe system model to process uncertainties in both subscriptions and publications. The system model is evaluated in an implementation of a publish/subscribe system supporting uncertainties in publications and subscriptions through an approximate matching semantic.
  • Keywords
    inference mechanisms; information dissemination; publishing; uncertainty handling; approximate matching; approximate matching semantic; enterprises application integration; location-based services; network management; publications; publish paradigm; selective information dissemination; subscribe paradigm; subscriptions; uncertainties; Application software; Computer network management; Computer science; Data models; Engineering management; Intelligent networks; Jacobian matrices; Prototypes; Subscriptions; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on
  • Print_ISBN
    0-7803-7866-0
  • Type

    conf

  • DOI
    10.1109/CIRA.2003.1222087
  • Filename
    1222087