Q-MAP: a novel multicast routing method in wireless ad hoc networks with multiagent reinforcement learning

Abstract

Multicast plays an important role in ad hoc networks, and multicast algorithms have the goal of directing traffic from sources to receivers maximizing some measure of network performance combining the processes of routing and resource reservation. This paper discusses some current literature about multicast routing in mobile ad hoc networks. Further, by investigating the swarm-based routing method and the multiagent reinforcement learning applications, this paper analyses the possibility and merit of adopting the reinforcement learning method in a multicast routing protocol for wireless ad hoc networks. And based on the above, this paper presents a novel multicast routing method, the Q-MAP algorithm, that ensures the reliability of the resource reservation in the wireless mobile ad hoc networks. The features and efficiency of the Q-MAP multicast routing method are also illustrated in this paper.