Data burst generation algorithm in optical burst switching networks

Abstract

This thesis presents a novel data burst generation algorithm using hysterisis characteristics in the queueing model, for the ingress edge node in optical burst switching networks. Simulation with Poisson and self-similar traffic models shows that this algorithm changes the data burst size adaptively in accordance with the offered load and offers high average data burst utilization with less timer operation. It also reduces the possibilities of continuous blocking problem in the bandwidth reservation request, limits the maximum queueing delay, and minimizes the required burst size by lifting up data burst utilization for the bursty input IP traffic.