dc.contributor.author | Kosunalp S. | |
dc.contributor.author | Chu Y. | |
dc.contributor.author | Mitchell P.D. | |
dc.contributor.author | Grace D. | |
dc.contributor.author | Clarke T. | |
dc.date.accessioned | 20.04.201910:49:12 | |
dc.date.accessioned | 2019-04-20T21:43:31Z | |
dc.date.available | 20.04.201910:49:12 | |
dc.date.available | 2019-04-20T21:43:31Z | |
dc.date.issued | 2016 | |
dc.identifier.issn | 0952-1976 | |
dc.identifier.uri | https://dx.doi.org/10.1016/j.engappai.2016.06.012 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12403/587 | |
dc.description.abstract | This paper studies the potential of a novel approach to ensure more efficient and intelligent assignment of capacity through medium access control (MAC) in practical wireless sensor networks. Q-Learning is employed as an intelligent transmission strategy. We review the existing MAC protocols in the context of Q-learning. A recently-proposed, ALOHA and Q-Learning based MAC scheme, ALOHA-Q, is considered which improves the channel performance significantly with a key benefit of simplicity. Practical implementation issues of ALOHA-Q are studied. We demonstrate the performance of the ALOHA-Q through extensive simulations and evaluations in various testbeds. A new exploration/exploitation method is proposed to strengthen the merits of the ALOHA-Q against dynamic the channel and environment conditions. © 2016 Elsevier Ltd | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier Ltd | |
dc.relation.isversionof | 10.1016/j.engappai.2016.06.012 | |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | ALOHA | |
dc.subject | Medium access control | |
dc.subject | Q-Learning | |
dc.subject | Wireless sensor networks | |
dc.subject | Access control | |
dc.subject | Wireless sensor networks | |
dc.subject | ALOHA | |
dc.subject | Environment conditions | |
dc.subject | Exploration/exploitation | |
dc.subject | Extensive simulations | |
dc.subject | Medium access control(MAC) | |
dc.subject | Q-learning | |
dc.subject | Q-learning approach | |
dc.subject | Transmission strategies | |
dc.subject | Medium access control | |
dc.subject | ALOHA | |
dc.subject | Medium access control | |
dc.subject | Q-Learning | |
dc.subject | Wireless sensor networks | |
dc.subject | Access control | |
dc.subject | Wireless sensor networks | |
dc.subject | ALOHA | |
dc.subject | Environment conditions | |
dc.subject | Exploration/exploitation | |
dc.subject | Extensive simulations | |
dc.subject | Medium access control(MAC) | |
dc.subject | Q-learning | |
dc.subject | Q-learning approach | |
dc.subject | Transmission strategies | |
dc.subject | Medium access control | |
dc.title | Use of Q-learning approaches for practical medium access control in wireless sensor networks | en_US |
dc.type | article | en_US |
dc.relation.journal | Engineering Applications of Artificial Intelligence | en_US |
dc.contributor.department | Bayburt University | en_US |
dc.contributor.authorID | 36975673200 | |
dc.contributor.authorID | 55532094000 | |
dc.contributor.authorID | 34571564500 | |
dc.contributor.authorID | 7004927899 | |
dc.contributor.authorID | 7202915655 | |
dc.identifier.volume | 55 | |
dc.identifier.startpage | 146 | |
dc.identifier.endpage | 154 | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |