Power aware agent based secure routing protocol for mobile ad hoc networks

Abstract

newline Mobile Ad-hoc Networks (MANETs) have gained a lot of attention in the recent years due to its wide range of applications in various areas of communication. Operation in MANETs requires no fixed infrastructure and network topology changes frequently. Routing in communication networks plays an important role and in dynamic environment like MANET, it becomes a more challenging task. In MANET, nodes are battery powered and communicate over wireless links to other nodes with implicit trusts which makes it open to attacks. Also, the routing operation consumes most of the energy which is approximately 70% of the total energy consumed. Hence, it becomes necessary to design energy efficient and secure routing protocols for MANETs to provide secure communication with a prolonged network lifetime. Many solutions have been proposed to solve the problems faced during routing in MANET; each of them possessing some benefits and drawbacks. These solutions need to be improved for achieving an optimum result with respect to various network parameters. Also a proper integration of the security algorithms with the routing algorithms have to be done to satisfy the security attributes like authenticity, confidentiality and integrity during communication to achieve security goals. Nowadays, Swarm Intelligence (SI) based routing protocols are choosen by the researchers to provide a potential solution for routing problems. Due to their dynamic and adaptive approach to solve the problems these protocols show better results in comparison with the traditional routing protocols. Collaboration of mobile agents helps in route discovery within an optimal time and in expense of less network resources. Associating security mechanisms with this approach makes the communication more secure. Ant Colony Optimization (ACO) is one of the mostly used SI based metahuristic approach. Biological antsand#8223; behaviour is studied and simulated to solve various complex combinatorial problems. ACO provides a decentralized, robust and resilent technique to provide solutions to optimisation problems applying reinforcement learning mechanism. These features of ACO are taken as an advantage to design routing protocols with optimal paths, higher performance and more reliability. Also, self organising capabilities of ACO routing protocols provide a higher performance over the traditional routing protocols. newlineviii newlineThis thesis contributes a complete simulation study of the basic routing protocols like AODV and DSR in the absence and presence of attack (we have considered blackhole attack as