Optimal Design of Optical Ring Networks with Differentiated Reliability (DiR)

Abstract

Current optical networks typically offer two degrees of service reliability: full protection in presence of a single fault in the network, and no protection at all. This situation reflects the historical duality that has its roots in the once divided telephone and data environment. The circuit oriented service required protection, i.e., provisioning of readily available spare resources to replace working resources in case of a fault. The datagram oriented service relied upon restoration, i.e., dynamic search for and reallocation of affected resources via such actions as routing table updates.The current development trend, however, is gradually driving the design of networks towards a unified solution that will jointly support traditional voice and data services as well as a variety of novel multimedia applications. The growing importance of concepts, such Quality of Service (QoS) and Differentiated Services that provide varying levels of service performance in the same network evidences this trend.Consistently with this pattern, the novel concept of Differentiated Reliability (DiR) is formally introduced in the paper and applied to provide multiple reliability degrees (classes) in the same network layer using a common protection mechanism, i.e., path switching. According to the DiR concept, each connection in the layer under consideration is guaranteed a minimum reliability degree, defined as the Maximum Failure Probability allowed for that connection. The reliability degree chosen for a given connection is thus determined by the application requirements, and not by the actual network topology, design constraints, robustness of the network components, and span of the connection.An efficient algorithm is proposed to design the Wavelength Division Multiplexing (WDM) layer of a DiR ring.KeywordsFailure ProbabilityWavelength Division MultiplexIEEE Communication MagazineAuxiliary GraphMean Time Between FailureThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.