Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic Engineering

Abstract

Wireless Sensor Networks (WSN) are commonly used to observe and monitor precise environments. WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments. The base station received the amount of data collected by the numerous sensors. The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale. The Trust-Based Adaptive Acknowledgement (TRAACK) Intrusion-Detection System for Wireless Sensor Networks (WSN) is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization (MPSO) has been proposed to predict knot confidence. Simulations were run for non-malicious networks (0% malicious) and different percentages of malicious nodes were discussed. The findings suggest that the proposed method TRAACK Modified Particle Swarm Optimization (MPSO) packet delivery rate outperforms TRAACKPSO by 3.3% with 0% malicious nodes. Similarly, the packet delivery rate of TRAACKMPSO is 30% malicious, 3.5% better than TRAACKPSO in WSN.