Enhanced Fallback+ : An Efficient Multiconstraint Path Selection Algorithm for QoS Routing

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Author(s)

    • KINOSHITA Kazuhiko
    • Department of Information Networking, Graduate School of Information Science and Technology, Osaka University
    • TANIOKA Hideaki
    • Department of Information Systems Engineering, Graduate School of Engineering, Osaka University
    • TAKINE Tetsuya
    • Department of Communication Engineering, Graduate School of Engineering, Osaka University
    • MURAKAMI Koso
    • Department of Information Networking, Graduate School of Information Science and Technology, Osaka University

Abstract

In future high-speed networks, provision of diverse multimedia services with strict quality-of-service (QoS) requirements, such as bandwidth, delay and so on, is desired. QoS routing is a possible solution to handle these services. Generally, a path selection for QoS routing is formulated as a shortest path problem subject to multiple constraints. However, it is known to be NP-complete when more than one QoS constraint is imposed. As a result, many heuristic algorithms have been proposed so far. The authors proposed a path selection algorithm Fallback+ for QoS routing, which focuses not only on the path selection with multiple constraints but also on the efficient use of network resources. This paper proposes an enhanced version of Fallbacks, named Enhanced Fallback+, where in a shrewd way, it keeps tentative paths produced in the conventional Fallback algorithm with Dijkstra's algorithm. Simulation experiments prove the excellent performance of Enhanced Fallbacks, compared with the original Fallback+ and other existing path selection algorithms.

Journal

  • IEICE Transactions on Communications, B

    IEICE Transactions on Communications, B 87(9), 2708-2718, 2004-09-01

    The Institute of Electronics, Information and Communication Engineers

References:  31

Cited by:  4

Codes

  • NII Article ID (NAID)
    110003222551
  • NII NACSIS-CAT ID (NCID)
    AA10826261
  • Text Lang
    ENG
  • Article Type
    Journal Article
  • ISSN
    09168516
  • Data Source
    CJP  CJPref  NII-ELS 
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