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High-speed communication systems require robust routing protocol. The selection and optimization of the routing protocol in Wavelength Division Multiplexed (WDM) optical networks decide utilization of bandwidth capacity offered by these networks. When Open Shortest Path First (OSPF) protocol is used for routing, link weight selection is one of the main concerns in order to optimize the routing. In this paper, OSPF link weight selection is performed through Ant Colony Optimization (ACO) and Evolutionary Algorithm (EA). The novelty of the work lies in the implementation of optimization techniques in offline network mode on networks of variable densities with an objective is to reduce utilization of bottleneck link, i.e., to reduce congestion. As a result, knowledge of optimization specific to type of network can be retained in online networking mode. ACO and EA are implemented on random network which is composed of 4 nodes and 5 links (4n5e), standard National Science Foundation NETwork (NSFNET), and standard COST 239 networks in order to test the optimization on networks of different densities. Maximum End-to-End (E2E) latency and bottleneck Link Utilization (LU) obtained after application of optimization techniques is compared for networks considered. It is observed that EA optimization has a better optimized denser network (COST 239) and ACO has optimized NSF and 4n5e networks better than EA optimization.

This study aims at highlighting OSPF (Open Shortest Path First) routing technique and its performance under different network failures. A single failure in high-speed networks even for fraction of second can disrupt millions of users. Therefore it is imperative to analyze performance of routing protocol under network failure. In this paper, OSPF routing technique is examined under single and multiple link failures. Investigations are performed on basis of average E2E (end to end) delay, throughput and jitter. In this investigation, convergence time for link failures is calculated. It is observed that network has least average E2E delay when working path does not experience any failure. Under single link failure, average E2E delay is least when failed link is nearest to the source node. Under double link failure, average E2E delay is maximum when failed links are farthest apart. Convergence time for multiple link failure is more than single link failure. It is observed that convergence is least for failed link immediately connected to the source node. As observed from plots, network achieves high throughput when working path does not experience any failure and throughput reduces for multiple link failures. Average jitter is maximum for the network without failure and its value reduces for multiple link failures. The investigations in this paper provide insight into the performance of OSPF routing technique. Analysis performed and values of performance metrics obtained for various link failures provide knowledge of critical links and backup routes with respect to application specific QoS (Quality of Service) requirements.

Network planning for existing as well as future high-speed networks is important for extracting best performance of networks. Network planning requires reliable traffic model which can serve constant as well as variable ingress traffic. In this paper, network performance is investigated with uniform and population-distance traffic models. Open Shortest Path First (OSPF) protocol is used for routing and link weight determination is a crucial task for this routing. Link weights in networks of different densities are optimized with an objective of minimizing network congestion. Ant Colony Optimization (ACO), Genetic Algorithm (GA) and Simulated Annealing (SAN) optimization techniques are applied to examine link weights of National Science Foundation NETwork (NSFNET) and standard COST 239 networks. The novelty of the work lies in investigations of network performance with different optimization techniques, traffic models and density. The outcome of this work can assist in optimizing overall network planning. Maximum latency and congestion of both networks are compared for each optimization and traffic model. It is observed that population-distance traffic modeling has reduced network congestion for both the networks but this traffic model has increased maximum latency of NSFNET. Performance of COST 239 network which is denser than NSFNET, has improved with population-distance traffic model w.r.t. congestion and latency.