A Reinforcement Learning-based Routing for Delay Tolerant Networks

Authors

Abstract

Delay Tolerant Reinforcement-Based (DTRB) is a delay tolerant routing solution for IEEE 802.11 wireless networks which enables device to device data exchange without the support of any pre-existing network infrastructure. The solution utilizes Multi-Agent Reinforcement Learning techniques to learn about routes in the network and forward/replicate the messages that produce the best reward. The rewarding process is executed by a learning algorithm based on the distances between the nodes, which are calculated as a function of time from the last meetings. DTRB is a flooding-based delay tolerant routing solution. The simulation results show that DTRB can deliver more messages than a traditional delay tolerant routing solution does in densely populated areas, with similar end-to-end delay and lower network overhead.

Keywords

Delay tolerant routing, Multi-agent systems, Reinforcement-learning, Gossip algorithms

Journal

Engineering Applications of Artificial Intelligence, August 2013

DOI