• DocumentCode
    2194996
  • Title

    Neuron-based connection acceptance strategy

  • Author

    Chen, Jian-Liang ; Tsai, Che-Hsien ; Jeng, Sheng-Ching ; Choy, Michael

  • Author_Institution
    Comput. & Commun. Res. Labs., Ind. Technol. Res. Inst., Hsinchu, Taiwan
  • fYear
    1995
  • fDate
    20-22 Jun 1995
  • Firstpage
    89
  • Lastpage
    94
  • Abstract
    A neural system with the back propagation learning algorithm is discussed for making decisions in connection management. The strategy is divided into two developed stages. In the learning stage, we collect three groups of information including the traffic description, QoS requirement, and link status, and then embed them in the input pool. The accept/reject decision for a requested service is generated in the output layer. Upon completing the learning stage, the on-line test is in progress. From the results, we found that the strategy can support the real-time feature in connection management. In addition, the QoS is guaranteed while the connection is permitted under our ATM testbed
  • Keywords
    asynchronous transfer mode; backpropagation; multimedia communication; neural nets; real-time systems; telecommunication computing; telecommunication congestion control; telecommunication network management; ATM testbed; QoS requirement; back propagation learning algorithm; call admission control; connection management; input pool; learning stage; link status; neural system; neuron-based connection acceptance strategy; on-line test; real-time feature; requested service; traffic description; Asynchronous transfer mode; B-ISDN; Communication system traffic control; Monitoring; Neural networks; Project management; Quality management; Quality of service; Telecommunication traffic; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Community Networking, 1995. Integrated Multimedia Services to the Home., Proceedings of the Second International Workshop on
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    0-7803-2756-X
  • Type

    conf

  • DOI
    10.1109/CN.1995.509557
  • Filename
    509557