Comparative Analysis of Trustworthiness in Swarm Intelligence Techniques using Mobile Adhoc Network Environment

Swarm Intelligence is a technique that deals with collective behaviour of decentralized and self-organized systems. For algorithm with complex problems, Swarm Intelligence is one of the successful paradigms. In this paper, an elaborate comparative study on trustworthiness is evaluated between two techniques of swarm intelligence and its hybrid: Ant Colony Optimization, Particle Swarm Optimization and hybridized Particle Swarm Optimization using a trust model in a simulated Mobile Adhoc Network environment. The effect of evaluating trustworthiness and discovering misbehaving nodes prior to interactions, as well as their influence on the network performance would be investigated. The results of investigating the trustworthiness evaluation and the network performance even in the presence of malicious nodes showing improvement of a hybridized Swarm Intelligence technique over other existing convectional swarm intelligence systems are shown.