A neural-based technique for estimating self-similar traffic average queueing delay
مقال من تأليف: Yousefi Zadeh, Homayoun ;
ملخص: 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.
لغة:
إنجليزية