QL-MAC : a Q-learning based MAC for wireless sensor networks

S. Galzarano, A. Liotta, G. Fortino

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

36 Citations (Scopus)
2 Downloads (Pure)


WSNs are becoming an increasingly attractive technology thanks to the significant benefits they can offer to a wide range of application domains. Extending the system lifetime while preserving good network performance is one of the main challenges in WSNs. In this paper, a novel MAC protocol (QL-MAC) based on Q-Learning is proposed. Thanks to a distributed learning approach, the radio sleep-wakeup schedule is able to adapt to the network traffic load. The simulation results show that QL-MAC provides significant improvements in terms of network lifetime and packet delivery ratio with respect to standard MAC protocols. Moreover, the proposed protocol has a moderate computational complexity so to be suitable for practical deployments in currently available WSNs.
Original languageEnglish
Title of host publicationAlgorithms and Architectures for Parallel Processing - Proceedings of the 13th International Conference, ICA3PP 2013, Vietri sul Mare, Italy, December 18-20, 2013. Part II
EditorsR. Aversa, J. Kolodziej, J. Zhang, F. Amato, G. Fortino
ISBN (Print)ISBN 978-3-319-03888-9
Publication statusPublished - 2013

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


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