Over the past decade there has been an exponential increase in the Internet traffic especially with the proliferation of cloud computing and other distributed data services. This explosion of data traffic with its dynamically changing traffic patterns and flows might result in degradation of the network performance. In this context, there is a need for an intelligent and efficient network management system that delivers guaranteed services. To this extent, this paper proposes BaProbSDN, a probabilistic Quality of Service (QoS) routing mechanism for Software Defined Networks (SDN).
The QoS routing algorithm employs the bandwidth availability metric as a QoS routing constraint for unicast data delivery. BaProbSDN makes use of Bayes’ theorem and Bayesian network model to determine the link probability in order to select the route that satisfies the given bandwidth constraint. The performance of the proposed probabilistic QoS routing algorithm was tested in a simulation-based environment and compared against the widest-shortest path routing (WSR) algorithm. The results demonstrate that BaProbSDN can achieve up to 8.02% decrease in the bandwidth blocking rate when compared to WSR in the presence of link update inaccuracies of threshold and time delay.