Traffic engineering and QoS control between wireless diffserv domains using PQ and LLQ

Numerous recent studies have proven that traffic patterns generated by multimedia services are different from traditional Poisson traffic. It has been shown that multimedia network traffic exhibits long-range dependency (LRD) and self-similar characteristics. The area of wireless IP traffic modeling in terms of providing assured QoS to the end-user is still immature and the majority of existing work is merely based on characterization of the wireless IP traffic without investigating the behavior of queueing systems under such traffic conditions. Work done in this area has been limited to simplified models of FIFO queueing systems which do not accurately reflect likely queueing system implementations or the results have been limited to simplified numerical analysis studies. In this paper, we contribute towards the solution of this problem by focusing on traffic engineering of different UMTS service classes by providing efficient QoS mapping using two common queueing disciplines; Priority Queueing (PQ) and Low Latency Queueing (LLQ), which are likely to be used in future all-IP based packet transport networks.The present study is based on a realistic traffic model which is long-range dependent and self-similar. We consider three different classes of self-similar traffic being fed to a queueing model of three queues based on a G/M/1 queueing system. We first make an analysis on the basis of non-preemptive priority and then on the basis of low-latency queuing and find closed form expressions of expected waiting times and packet loss rates of different traffic classes. In order to validate our models we conduct a series of experiments. We have developed a comprehensive discrete-event simulator for a G/M/1 queueing system in order to understand and evaluate the QoS behavior of self-similar traffic and carry out performance evaluations of multiple classes of input traffic in terms of expected queue length, packet delay and packet loss rate. Furthermore, we have developed a traffic generator to realize our self-similar traffic model and use it to feed traffic through a CISCO router-based test bed. The results obtained from the two different queueing schemes (PQ and LLQ) are then compared with the simulation results to ascertain the accuracy of our model.