MLA-RPM: A Machine Learning Approach to enhance trust for secure Routing Protocol in Mobile Ad hoc networks

Abstract

            The network is the growing area in the field of telecommunication in which Mobile Ad Hoc Networks (MANETs) is one of the emerging fields. This is the area, which is used everywhere in telecommunication, war zone, gaming, etc. to improve the user's experience. Soon it will be commercialized on the large scale due to its versatile nature.  MANETs operates with very limited infrastructures that include its communication hardware, power sources, a fixed software program. Due to this limitation, MANET is having limited working especially routing behavior.  To overcome this situation, we now propose a method including a learning algorithm through which we can optimize the routing conditions and can improve the performance of MANET. In this work, we are trying to fill the research gap between deep learning and wireless networking. We have gone through the state-of-the-art algorithm to identify the possible area of research.  The overall simulation result shows that the cost of the routing and overall maintenance of the communication has reduced and we found better results.