Fuzzy adaptive predictive flow control of ATM network traffic

Bor Sen Chen*, Yu Shuang Yang, Bore Kuen Lee, Tsern-Huei Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


In order to exploit the nonlinear time-varying property of network traffic, the traffic flow from controlled sources is described by a fuzzy autoregressive moving-average model with auxiliary input (fuzzy ARMAX process), with the traffic flow from uncontrolled sources (i.e., cross traffic) being described as external disturbances. In order to overcome the difficulty of the transmission delay in the design of congestion control, the fuzzy traffic model is translated to an equivalent fuzzy predictive traffic model. A fuzzy adaptive flow control scheme is proposed to avoid congestion at high utilization while maintaining good quality of service. By use of fuzzy adaptive prediction technique, the difficulties in congestion control design due to nonlinearity, time-varying characteristics, and large propagation delay can be overcome by the proposed adaptive traffic control method. A comparative evaluation is also given to show the superiority of the proposed method.

Original languageEnglish
Article number1220302
Pages (from-to)568-581
Number of pages14
JournalIEEE Transactions on Fuzzy Systems
Issue number4
StatePublished - 1 Aug 2003


  • Asynchronous transfer mode (ATM) traffic control
  • Fuzzy ARMAX process
  • Fuzzy predictive model
  • Stochastic fuzzy systems

Fingerprint Dive into the research topics of 'Fuzzy adaptive predictive flow control of ATM network traffic'. Together they form a unique fingerprint.

Cite this