Q-Learning-Driven Enhancement of Slotted ALOHA in IEEE 802.15.4 WSNs

Baptista, Amilton; Velez, Fernando J.

Publication

Q-Learning-Driven Enhancement of Slotted ALOHA in IEEE 802.15.4 WSNs

2024-07Conference object

dc.contributor.author	Baptista, Amilton
dc.contributor.author	Velez, Fernando J.
dc.date.accessioned	2024-06-11T08:28:08Z
dc.date.available	2024-06-11T08:28:08Z
dc.date.issued	2024-07
dc.description.abstract	Given the proliferation of connected devices and the prioritization of real-time data acquisition across various scenarios, enhancing the energy efficiency within Wireless Sensor Networks (WSNs) is of paramount importance. This work has focused on the IEEE 802.15.4 standard and addresses existing medium access control protocols such as CSMA or Slotted ALOHA and proposes refinements in the Slotted ALOHA protocol through incorporating techniques like Binary Exponential Backoff (BEB) and Q-learning. These enhancements have demonstrated to be promising in terms of average delay reduction, energy efficiency and bolstered network throughput. As it facilitates more efficient energy management it constitutes a robust alternative to conventional CSMA in WSN MAC sub-layer protocols.	pt_PT
dc.description.version	info:eu-repo/semantics/acceptedVersion	pt_PT
dc.identifier.citation	Amilton Venâncio Baptista, Fernando J. Velez, “Q-Learning-Driven Enhancement of Slotted ALOHA in IEEE 802.15.4 WSNs,” in Proc. of IEEE International Mediterranean Conference on Communications and Networking – MeditCom 2024, Madrid, Spain, Jul, 2024.	pt_PT
dc.identifier.uri	http://hdl.handle.net/10400.6/14428
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	IEEE	pt_PT
dc.relation	Instituto de Telecomunicações
dc.relation	New RAN TEchniques for 5G UltrA-dense Mobile networks
dc.rights.uri	http://creativecommons.org/licenses/by-nd/4.0/	pt_PT
dc.subject	Wireless Sensor Networks	pt_PT
dc.subject	IEEE 802.15.4	pt_PT
dc.subject	Slotted ALOHA	pt_PT
dc.subject	Q-ALOHA	pt_PT
dc.subject	Binary Exponential Backoff	pt_PT
dc.subject	Medium Access Control Protocols	pt_PT
dc.subject	Latency	pt_PT
dc.subject	Energy Efficiency	pt_PT
dc.title	Q-Learning-Driven Enhancement of Slotted ALOHA in IEEE 802.15.4 WSNs	pt_PT
dc.type	conference object
dspace.entity.type	Publication
oaire.awardTitle	Instituto de Telecomunicações
oaire.awardTitle	New RAN TEchniques for 5G UltrA-dense Mobile networks
oaire.awardURI	info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PT
oaire.awardURI	info:eu-repo/grantAgreement/EC/H2020/813391/EU
oaire.citation.conferencePlace	Madrid. Spain	pt_PT
oaire.citation.title	IEEE International Mediterranean Conference on Communications and Networking – MeditCom 2024	pt_PT
oaire.fundingStream	6817 - DCRRNI ID
oaire.fundingStream	H2020
person.familyName	Baptista
person.familyName	Velez
person.givenName	Amilton
person.givenName	Fernando J.
person.identifier	C3WdfREAAAAJ&hl
person.identifier.ciencia-id	3F13-47A7-C2C3
person.identifier.ciencia-id	1510-E247-C9DB
person.identifier.orcid	0009-0002-1198-8520
person.identifier.orcid	0000-0001-9680-123X
project.funder.identifier	http://doi.org/10.13039/501100001871
project.funder.identifier	http://doi.org/10.13039/501100008530
project.funder.name	Fundação para a Ciência e a Tecnologia
project.funder.name	European Commission
rcaap.rights	openAccess	pt_PT
rcaap.type	conferenceObject	pt_PT
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