Optimistic Attack Detection Using Triangular Mutation based Particle Swarm Optimization in Wireless Multimedia Sensor Networks

To detect the attack, a Novel Triangular mutation based Particle Swarm Optimization with attack detection ADOV technique has been proposed. The Ad Hoc On-Demand Distance Vector (AODV) algorithm is using the connectivity concept to decide between source and local repair when a link break occurs. Besides, we used a Computational Intelligence algorithm, called Particle Swarm Optimization (PSO), which enables to find candidate solutions in all considered search space in order to reduce average data packet drop ratio over the network. The performance of the original TIGMR protocol based geographic multipath routing is compared with this new implemented approach, called here as AODV-PSO. Two metrics were used to evaluate the performance of the algorithm: Packet drop ratio and throughput. We observed that the AODV-PSO outperformed the original AODV protocol in the scenarios studied in this paper.