Abstract:
With the rapid development of Internet, mobile networks and high-performance networking technology, QoS multicast routing in networks- has become a very important research issue in the areas of networks and distributed systems and considered as a challenging and hard problem for the next generation Internet and high-performance networks. This dissertation discusses the heuristic algorithms for multicast routing problem with multiple QoS constraints in networks. In this dissertation, Evolutionary Algorithms like Ant and Genetic Algorithms are developed that are capable to deal effectively by issues related with multicast routing for the internet and can provide QoS-sensitive paths in a scalable and flexible way. A multicast tree selection algorithm based on Non-dominated Sorting technique of Genetic Algorithms is also discussed to simultaneously optimize multiple QoS parameters. These algorithms optimize the network resources like end-to-end-delay and delay jitter, and can converge to the optimal or near-optimal solution within a few iteration, even for the network environment with uncertain parameters. The incremental rate of the computational cost of these algorithms can be close to polynomial and is less than exponential rate. The simulations carried out shows that these heuristic algorithms converge to the near optimal solutions in lesser number of iterations. Among these algorithms, Ant Algorithm converges faster than the Genetic Algorithms. The scalability of these algorithms especially, the Ant Algorithm, proved to be noteworthy when compared to the traditional QoS multicast routing algorithms
