Dynamic grooming, routing, and wavelength assignment for real-time optical networks

One of the major problems facing optical networking is to intelligently assign physical resources such as lightpaths and regenerators to connection requests, namely the grooming, routing and wavelength assignment (GRWA) problem. Due to the high computation complexity, many heuristic methods have been proposed to solve the problem. We first propose an extended Dijkstra shortest path algorithm to solve GRWA for dynamic network while considering regeneration, quality of transmission (QoT), mixed-line-rate (MLR) and traffic grooming. This generalized adaptive shortest path (GASP) algorithm requires that each node maintain global view of network state information. In order to perform GRWA in a distributed fashion, which allows for greater network scalability, and gives individual domains more control over their data, we then apply an ant colony optimization (ACO) technique, a metaheuristic optimization algorithm used to solve dynamic problems, to real-time optical networks. We compare the two proposed algorithms and show that the ACO algorithm outperforms the GASP algorithm in terms of connection request blocking probability and network throughput while maintaining a reasonable computation complexity.