QoS Improvement using Enhanced Manhattan Mobility Model on Proposed Ant in MANETs

In the current Mobile Ad-hoc Network (MANET) route discovery procedure, traffic overflow and overhead may pose a major challenge for a path finding between communicating nodes. Swarm intelligence technique has been applied for various routing problems. We suggest an ant-based bottleneck routing method for MANET to identify weak links in the chosen route for routing overhead and delay issues. During data exchange, it selects the route using a swarm based technique called Ant Colony Optimization (ACO). Initially, we have created node movements by Enhanced Manhattan Mobility Model (EMMM) and then a bottleneck value based ant colony optimization technique is applied. The simulation results show the improvement over existing ACO technique in terms of mobility and pause time. The Quality of Service (QoS) performance metrics showed improvement of 66% in drop rate, 141% in the packet delivery ratio, 42% in packet overhead, 171% in throughput, and 34% in the average end-to-end delay for mobility experiment. There is an improvement of 82% in drop rate, 108% in the packet delivery ratio, 45% in packet overhead, 171% in throughput, and 49% in the average end-to-end delay for a pause time experiment.