Supporting QoS aware Multicasting in Network Applications

Abstract

The increase in demand of several new generation applications over Internet becomes an important issue and challenge. These applications require data either to be transmitted from one source to many receivers or many sources to many receivers. The multicast routing is proposed as one of the vital mechanisms to communicate a message from one source to multiple receivers or multiple sources to multiple receivers. The applications involving one-to-many data transmission requires to build tree structure spanning over the sender and receivers. Building up such a tree satisfying multiple requirements like delay, multicast delay variation, bandwidth and loss probability is NP- Complete. Though many heuristics have been proposed in the recent literatures to solve this problem, still finding an optimal multicast tree with multiple constraints in polynomial time is a nontrivial task. This motivates us to take up research to propose efficient meta-heuristics for constructing QoS-aware source based multicast tree under multiple constraints. For many-to-many applications, the core based tree (CBT) has the advantage over source based tree because in CBT only one entry is required for all sources. The sources transmit the data to the receivers through the core node. The real time messages transmitted over the CBT requires the optimal placement of the core node so that the messages can be transmitted to all the receivers within a restricted time and also at the same time. Many algorithms have been devised during past to discover the best location of core for the smooth delivery of real-time messages. However, finding the optimal placement of core still remains a challenge till date. This motivates us to work in this direction for finding the best position of core node for QoS-aware multicasting in network multimedia applications. newlineIn this thesis, first the source based multicast routing task is formulated as a single objective task. First we present an efficient hybrid bacteria foraging and particle swarm optimization algorithm