Performance analysis of prioritized Automatic Repeat-request systems in the presence of self-similar traffic

Automatic Repeat reQuest (ARQ) is a promising forward error control mechanism for improving the reliability of data transmission over wireless channels. Traffic self-similarity has been discovered to be a ubiquitous phenomenon in communication networks with a significant impact on the network performance and user-perceived Quality-of-Service (QoS). However, due to the high complexity and challenges of modelling traffic self-similarity, there has not been any analytical model reported for ARQ under self-similar traffic. To fill this gap, we develop a novel analytical model of multi-buffer ARQ systems in the presence of prioritized self-similar traffic for reliable data transmission and QoS differentiation. This model can be used to investigate the probabilities of queueing loss and transmission loss in the multi-buffer ARQ systems. The validity of the analytical model is demonstrated via extensive comparison between analytical and simulation results. The model is further adopted to investigate the effects of service capacity and delay bound of ARQ on the system performance.