• DocumentCode
    357687
  • Title

    An intelligent fuzzy routing scheme for improving ATM network performance using violation tagging function

  • Author

    Barolli, Leonard ; Koyama, Akio ; Yamada, Takako ; Yokoyama, Shoichi

  • Author_Institution
    Dept. of Public Policy & Social Studies, Yamagata Univ., Japan
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    5
  • Lastpage
    9
  • Abstract
    In ATM networks, traffic control design is major challenge because of the diverse services and the need for efficient network resource engineering. To cope with rapidly changing network conditions, traffic control methods for high speed networks must be adaptive, flexible, and intelligent for efficient network management. The use of intelligent algorithms based on fuzzy logic, neural networks and genetic algorithms can be efficient for traffic control in ATM networks. We propose a routing scheme which is based on fuzzy logic. The proposed scheme of routing the tagged cells can improve network utilization. Performance evaluation via simulations shows that the DPFC decision is very close to the ideal decision. The DPFC and FRM were able to send to the destination node 31% and 54% of tagged cells, respectively
  • Keywords
    asynchronous transfer mode; digital simulation; fuzzy logic; genetic algorithms; neural nets; telecommunication computing; telecommunication congestion control; telecommunication network routing; ATM network performance improvement; fuzzy logic; genetic algorithms; high speed networks; intelligent algorithms; intelligent fuzzy routing scheme; network management; neural networks; simulations; traffic control design; violation tagging function; Adaptive control; Adaptive systems; Design engineering; Fuzzy logic; High-speed networks; Intelligent networks; Neural networks; Programmable control; Routing; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications, 2000. Proceedings. 11th International Workshop on
  • Conference_Location
    London
  • ISSN
    1529-4188
  • Print_ISBN
    0-7695-0680-1
  • Type

    conf

  • DOI
    10.1109/DEXA.2000.874996
  • Filename
    874996