Multicast dynamic traffic grooming using bin packing method in WDM mesh networks

With the development of multimedia services in Internet technology, there comes a big gap between bandwidth utilization and the blocking probability for multicast requests in the optical wavelength division multiplexing (WDM) networks. The objective of the proposed approach is to minimize the number of requests blocked in a dynamic multicast optical networks by minimizing the total resources (such as transceivers, splitters and wavelengths) used by the requests and simultaneously increase the bandwidth utilization. Since there are multiple wavelengths on a WDM optical fiber of fixed capacities, minimizing the number of wavelengths to be used is a variation of the bin packing problem. In the bin packing problem, multicast requests of different granularities or subwavelengths must be packed into a finite number of wavelength channels, in such a fashion that it minimizes the number of wavelengths used. In computational complexity theory, it is a combinatorial NP-hard problem. Therefore, we propose two heuristic approaches that provide the efficient resource utilization. These algorithms are called Multicast Traffic Grooming with Bin packing Best-Fit (MTG-BBF) and Multicast Traffic Grooming with Bin packing First-Fit (MTG-BFF). Both the algorithms are derived from standard Bin pack heuristic approach and we map our problem with such kind of approach. Our simulations demonstrated that both the algorithms significantly reduce the blocking probability (BP) compared to well known existing algorithms and MTG-BFF produces slightly better performance than MTG-BBF in the standard networks.