APPLICATION OF SWARM INTELLIGENCE PSO TECHNIQUE FOR ANALYSIS OF MULTIMEDIA TRAFFIC AND QOS PARAMETERS USING OPTIMIZED LINK STATE ROUTING PROTOCOL

Mobile ad hoc network (MANET) nodes include wireless transmitters and receivers. At a given point in time, depending on the positions of the nodes, their transmitter and receiver coverage patterns, communication power levels and co-channel interference levels, a wireless connectivity in the form of a random, multi hop graph or “ad hoc" network exists among the nodes. In this research, it is proposed to modify OLSR using swarm intelligence, Particle Swarm Optimization (PSO), to reduce end to end delay and improve throughput in the network by traffic shaping at the network layer. The PSO algorithm represents each solution as a ‘bird’ in the search space and is referred to as ‘particle’. It uses the objective function to evaluate its candidate solutions, and operates on the resultant fitness values. Candidate solution and its estimated fitness, and velocity give the position of the particle. It also remembers the best fitness value it achieved till then during the algorithm’s operation which is usually referred to as the individual best fitness, and the candidate solution that achieved this fitness, is the individual best position ‘pbest’. The best fitness value attained among all particles in the swarm which is called global best fitness, and the candidate solution that attained this fitness, which is called the global best position or global best candidate solution ‘gbest’. OLSR generates link state information through nodes elected as Multi Point Relays (MPRs). It is proposed to modify OLSR using particle swarm optimization to reduce end to end delay and improve network throughput.