Resource planning in optical OFDM networking with traffic grooming technique

Abstract

Development of natural computation methods brought a new paradigm in solving real-world optimization problems, namely metaheuristic methods. Metaheuristics based on principles of swarm intelligence are currently widely considered by the research community and engineers in solving a whole range of intractable problems related to network planning and operating problems. Swarm intelligence as the discipline of artificial intelligence investigates individuals’ actions in multi-agent systems. With the intention to show that metaheuristics could be successfully applied in telecommunications, we used Bee Colony Optimization (BCO) metaheuristic in solving the planning and dimensioning problems in optical networking. BCO relies on principles of bee swarm intelligence. 5G generation of optical networking brings the opportunity to a network to be elastic or flexible, i.e. the resources are occupied according to bandwidth on demand. To save network resources, such as spectrum or transmitters, various traffic engineering techniques could be applied. Our focus of interest is the traffic grooming technique applied at the optical layer. Incorporating the grooming technique into the BCO optimization logic, we proposed the model for minimizing the number of transmitters by maximizing its capacity utilization. The results indicate that by applying the grooming technique a significant number of transmitters could be saved and accordingly, power efficiency could be improved.