A reinforcement learning-based routing for delay tolerant networks
Delay Tolerant Reinforcement-Based (DTRB) is a delay tolerant routing solution for IEEE 80231 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. (C) 2013 Elsevier Ltd. All rights reserved.
delay tolerant routing multi-agent systems reinforcement-learning gossip algorithms