Optimizing fairness and blocking probability for optical networks

In the study of dynamic routing and wavelength assignment (DRWA) algorithms and protocols in optical networks, blocking probability is a chief criterion for performance evaluation. But it does not always capture the full effect of a particular algorithm on other aspects, such as fairness problem, which refers to the variability in blocking probabilities experienced by connection requests between various node pairs. Most commercial routing protocols, such as OSPF, prefers to adopt the shortest path for a particular connection, also brings unfairness to diverse connection requests, and such an unfairness becomes more serious in optical networks without wavelength conversion due to wavelength continuity constraint. Some literature have concerned this fairness problem and proposed several fairness enhancement methods. But unfortunately, they will deteriorate the overall blocking probability. In this paper, we try to optimize the fairness and blocking probability simultaneously via the alternate routing strategy, and a novel classified alternate routing (CAR) approach will be adopted. In our investigations, we will consider the optimization of alternate path set determination strategy, wavelength assignment and path selection method, and link weight function, etc. Comparisons and collaborations with formerly proposed fairness enhancement methods will be also presented