Prediction-based routing through least cost delay constraint

Summary form only given. To control data network for a delay constraint application, it is necessary to understand the behavior of packet delay and the network traffic. In data network, the type of service (TOS) bits are included in the IP header to allow a router to construct various shortest path first (SPF) trees on various quality of service (QoS) needs (e.g., minimum delay). The average queueing delay is a major contributor to the packet delay due to the fact that the queueing delay increases rapidly as the utilization of a router increases. A number of studies of traffic measurements have established the presence of self-similarity that causes performance degradation including amplified queueing delay. A cost function is proposed to determine a metric in a routing table through the prediction of the average queueing delay. From this, the end-to-end packet delays in a simple data network are analyzed by applying prediction-based routing through a cost function using least cost delay constraint. By comparing the average packet delay of TOS 0 (default) routing with that of prediction-based TOS 16 (minimize delay) routing, we can demonstrate the performance improvement on the average packet delay with the presence of self-similar traffic.