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Ass. Lect. Ola Ashour Mohammed Mohammed :: Publications:

Title:
Reliable Multicast Routing Protocol Based on Reinforcement Learning
Authors: Ola Ashour; Thomas Kunz; Marc St.Hilaire
Year: 2023
Keywords: Reinforcement learning, Multicast routing, Mul- ticast tree, Wireless ad-hoc networks.
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: 1 -- 7
Publisher: IEEE
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

This paper proposes a reliable multicast routing protocol based on Q-learning for wireless ad-hoc networks. The proposed protocol has two goals: 1) enhance the reliability of data delivery and 2) reduce the overhead caused by multicast routing. To achieve these goals, the protocol uses link reliability as a routing metric. The protocol chooses the most reliable path for data transmission based on its Q-value. In addition, it continuously updates the Q-value of active paths and proactively switches to another path if the current path becomes less reliable. To evaluate the performance of the proposed protocol, simulations were conducted using Network Simulator 3 (NS-3). The performance of the proposed protocol was compared with the Multicast Ad-hoc On-demand Distance Vector (MAODV) protocol. The simulation results show that the proposed protocol effectively enhances reliability as it outperforms the MAODV routing protocol in terms of Packet Delivery Ratio (PDR). Moreover, it reduces the control overhead caused by multicast routing.

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