Title :
On prediction of bursty traffic in broadband satcom systems
Author :
Mehrvar, H.R. ; Le-Ngoc, T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada
Abstract :
For the purpose of traffic control in broadband satcom systems, it is required to predict the traffic descriptor for the next two round trip delay. The predicted traffic descriptor is used by earth-stations to shape their traffic in order to minimize traffic loss in the downlink queue and maximize the uplink utility. The paper investigates the application of neural networks or adaptive neuro fuzzy inference systems (ANFIS) in the prediction of bursty traffic and also application of neural networks in deriving the traffic descriptor. The result shows that the neural network approach is adequate for real time prediction of the traffic descriptor
Keywords :
adaptive systems; broadband networks; delays; fuzzy neural nets; inference mechanisms; multilayer perceptrons; neural net architecture; prediction theory; queueing theory; radio links; satellite communication; telecommunication congestion control; telecommunication traffic; adaptive neuro fuzzy inference systems; broadband networks; broadband satcom systems; bursty traffic prediction; downlink queue; multilayer neural network; multimedia satellite communication; neural network architecture; real time prediction; round trip delay; satellite earth stations; traffic descriptor; traffic loss; traffic shaping; uplink utility; Adaptive systems; Communication system traffic control; Delay; Downlink; Fuzzy neural networks; Fuzzy systems; Neural networks; Shape; Telecommunication traffic; Traffic control;
Conference_Titel :
Communications, 1996. ICC '96, Conference Record, Converging Technologies for Tomorrow's Applications. 1996 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
0-7803-3250-4
DOI :
10.1109/ICC.1996.541315
