A Neural-Based Technique for Estimating Self-Similar Traffic Average Queueing Delay
- Author(s): Yousefi'zadeh, Homayoun
- et al.
Published Web Locationhttp://ieeexplore.ieee.org/iel5/4234/22334/01042230.pdf?tp=&arnumber=1042230&isnumber=22334
Estimating buffer latency is one of the most important challenges in the analysis and design of traffic control algorithms. In this paper a novel approach for estimating average queueing delay in multiple source queueing systems is introduced. The approach relies on the modeling power of neural networks in predicting self-similar traffic patterns in order to determine the arrival rate and the packet latency of low loss, moderately loaded queueing systems accommodating such traffic patterns.