A reinforcement learning-based routing for delay tolerant networks |
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Authors: | Vitor G. Rolla Marilia Curado |
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Affiliation: | CISUC, Departamento de Engenharia Informática, Universidade de Coimbra, Pólo II, Pinhal de Marrocos, 3030-290 Coimbra, Portugal |
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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. |
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Keywords: | Delay tolerant routing Multi-agent systems Reinforcement-learning Gossip algorithms |
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