Dynamic RWA based on the combination of mobile agents technique and genetic algorithm in WDM networks with sparse wavelength conversion

In this paper, we study the dynamic RWA problem in WDM networks with sparse wavelength conversion and propose a novel hybrid algorithm for it based on the combination of mobile agents technique and genetic algorithm. By keeping a suitable number of mobile agents in the network to cooperatively explore the network states and continuously update the routing tables, the new hybrid algorithm has the ability to promptly determine the first population of routes for a new request based on the routing table of its source node without requiring the time consuming process associated with the available GA-based dynamic RWA algorithms. To achieve a good load balance in WDM networks with sparse wavelength conversion, we adopt in our hybrid algorithm a new reproduction scheme and a new fitness function that simultaneously takes into account the path length, number of free wavelengths and wavelength conversion capability in route selection. Our new algorithm has the capabilities of achieving a better load balance and resulting a significantly lower blocking probability than that of the promising fixed-alternate routing algorithm for both the optical networks with sparse and full-range wavelength converters and the optical networks with sparse and limited-range wavelength converters, as verified by an extensive simulation study upon the ns-2 network simulator. The ability to guarantee both a low blocking probability and a small setup delay makes the new hybrid dynamic RWA algorithm very attractive for both the optical circuit switching networks and future optical burst switching networks.