• DocumentCode
    968128
  • Title

    Neural networks for adaptive traffic control in ATM networks

  • Author

    Nordström, Ernst ; Carlström, Jakob ; Gällmo, Olle ; Asplund, Lars

  • Author_Institution
    Uppsala Univ., Sweden
  • Volume
    33
  • Issue
    10
  • fYear
    1995
  • fDate
    10/1/1995 12:00:00 AM
  • Firstpage
    43
  • Lastpage
    49
  • Abstract
    Neural networks (NNs) have several valuable properties for implementing ATM traffic control. The authors present NN-based solutions for two problems arising in connection admission control, affecting the grade of service (GOS) at both the cell and call levels, and propose that neural networks may increase the network throughput and revenue
  • Keywords
    adaptive control; asynchronous transfer mode; channel capacity; neural nets; telecommunication computing; telecommunication congestion control; telecommunication network routing; telecommunication traffic; ATM networks; GOS; adaptive traffic control; connection admission control; learning; link allocation; network throughput; neural networks; revenue; routing; Adaptive control; Adaptive systems; Asynchronous transfer mode; Communication switching; Communication system traffic control; Intelligent networks; Neural networks; Programmable control; Switches; Traffic control;
  • fLanguage
    English
  • Journal_Title
    Communications Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    0163-6804
  • Type

    jour

  • DOI
    10.1109/35.466218
  • Filename
    466218
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=968128