Title :
Fuzzy modeling and prediction of network traffic fluctuations
Author :
Scheffer, M.F. ; Beneke, J.J.P. ; Kunicki, J.S.
Author_Institution :
Fac. of Eng., Rand Afrikaans Univ., Johannesburg, South Africa
Abstract :
Network management is a real-time observation and control action to optimize the grade of service of a network. More emphasis is being placed on the intelligent automatic exchange for stored program controlled (SPC) systems that are capable of real-time network management. The modeling of traffic characteristics and the prediction of future traffic flow are the first steps to efficient network control and management. This paper presents a fuzzy logic self-learning model and adaptive predictor of traffic now. The results of an application of this predictor on real world telephone links, are shown, and are compared to applications of a math-model and a Kalman-filter predictor
Keywords :
Kalman filters; filtering theory; fuzzy set theory; prediction theory; telecommunication congestion control; telecommunication network management; telecommunication services; telecommunication traffic; telephone networks; unsupervised learning; Kalman-filter predictor; SPC systems; adaptive predictor; fuzzy logic self-learning model; fuzzy modeling; grade of service; intelligent automatic exchange; math-model; network control; network traffic fluctuations; real-time control; real-time network management; real-time observation; stored program controlled; telephone links; traffic characteristics modeling; traffic flow prediction; Automatic control; Communication system traffic control; Control systems; Fluctuations; Fuzzy logic; Intelligent networks; Predictive models; Real time systems; Telecommunication traffic; Traffic control;
Conference_Titel :
Communications and Signal Processing, 1994. COMSIG-94., Proceedings of the 1994 IEEE South African Symposium on
Conference_Location :
Stellenbosch
Print_ISBN :
0-7803-1998-2
DOI :
10.1109/COMSIG.1994.512434
