An Efficient Algorithm for Delay and Delay- Variation Bounded Core Based Tree Generation

Many multimedia group applications require the construction of multicast tree satisfying the quality of service (QoS) requirements. To support real time communication, computer networks need to optimize the Delay and Delay-Variation Bounded Multicast Tree (DVBMT). The problem is to satisfy the end-to-end delay and delay-variation within an upper bound. The DVBMT problem is known to be NP complete. In this paper, we propose an efficient core selection algorithm for satisfying the end-to-end delay and delay-variation within an upper bound. The efficiency of the proposed algorithm is validated through the simulation. The simulation results reveal that our algorithm performs better than the existing heuristic algorithms

A hybrid ACO/PSO based algorithm for QoS multicast routing problem

AbstractMany Internet multicast applications such as videoconferencing, distance education, and online simulation require to send information from a source to some selected destinations. These applications have stringent Quality-of-Service (QoS) requirements that include delay, loss rate, bandwidth, and delay jitter. This leads to the problem of routing multicast traffic satisfying QoS requirements. The above mentioned problem is known as the QoS constrained multicast routing problem and is NP Complete. In this paper, we present a swarming agent based intelligent algorithm using a hybrid Ant Colony Optimization (ACO)/Particle Swarm Optimization (PSO) technique to optimize the multicast tree. The algorithm starts with generating a large amount of mobile agents in the search space. The ACO algorithm guides the agents’ movement by pheromones in the shared environment locally, and the global maximum of the attribute values are obtained through the random interaction between the agents using PSO algorithm. The performance of the proposed algorithm is evaluated through simulation. The simulation results reveal that our algorithm performs better than the existing algorithms