ANALYSIS OF JAMMING ATTACK IN MANET USING ENHANCED TIME DIVISION MULTIPLE ACCESS AND ENHANCED ARTIFICIAL BEE COLONY (ETDABC) APPROACH

Jammer is defined as an individual who is intentionally obstructing the legal wireless communication. There are many different attack strategies an adversary can use to jam wireless communications. The jammers considered for this research work is academic models. To improve the overall performance and the detection of jammers, this research work introduces swarm intelligence based algorithm to solve the jamming attack in MANET. The intelligent algorithms are deployed in MANET to apperceive the changes in network topology, the network communication flow, and each node's energy state. The main contribution of the present research work is the introduction of swarm intelligent algorithms like Enhanced Ant Colony Optimization (EACO), Enhanced Artificial Bee Colony (EABC) Algorithm and Enhanced Time Division Multiple Access and Enhanced Artificial Bee Colony (ETDABC). These swarm intelligent algorithms are more flexible and improve the searching capability of the algorithms.