Energy efficient medium access control protocol for data collection in wireless sensor network: a q-learning approach

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dc.authoridKorhan Cengiz / 0000-0001-6594-8861en_US
dc.authorscopusidKorhan Cengiz / 56522820200en_US
dc.authorwosidKorhan Cengiz / HTN-8060-2023en_US
dc.contributor.authorSah, Dinesh Kumar
dc.contributor.authorAmgoth, Tarachand
dc.contributor.authorCengiz, Korhan
dc.date.accessioned2022-11-07T07:49:21Z
dc.date.available2022-11-07T07:49:21Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractIn emerging business markets, the data is becoming new gold for the industries. There are several places such as marketing, manufacturing, and analysis of future trends becoming data-intensive to achieve growth. The tiny sensor placements in the field, cities, industry, buildings and sea are helping to collect data and process it either for information retrieval or decision making. The periodic scheduling of radio transceivers assists in accomplishing efficient energy utilization in sensors often uses Time-division multiple access (TDMA) protocols for node scheduling. Our objective is to reduce the amount of time; the receiver node is in the wake-up state. Besides, the slot which potentially not being used for an extended period can utilize by other nodes. The efficient utilization of slots can help to achieve low power duty cycles with low latency. To accomplish that, we propose the emulation of the classroom learning environment with the Q-learning grading for node scheduling. We proposed an analytical mapping of WSNs to classroom learning. The initial benchmark of the performance has compared to the IEEE.802.11 (TDMA-scheduling). Further, the TDMA driven protocols such as Z-MAC, learning-driven protocols (E-MAC or aloha-Q), i-Queue are compared to evaluate the parameters such as energy consumption, throughput, and latency.en_US
dc.identifier.citationSah, D. K., Amgoth, T., & Cengiz, K. (2022). Energy efficient medium access control protocol for data collection in wireless sensor network: A Q-learning approach. Sustainable Energy Technologies and Assessments, 53 doi:10.1016/j.seta.2022.102530en_US
dc.identifier.doi10.1016/j.seta.2022.102530en_US
dc.identifier.scopus2-s2.0-85136140694en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1016/j.seta.2022.102530
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3249
dc.identifier.volume53en_US
dc.identifier.wosWOS:000867847500001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorCengiz, Korhan
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofSustainable Energy Technologies and Assessmentsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectInternet of Thingsen_US
dc.subjectMAC Protocolsen_US
dc.subjectQ-learningen_US
dc.subjectScheduling Algorithmen_US
dc.subjectWireless Sensor Networksen_US
dc.titleEnergy efficient medium access control protocol for data collection in wireless sensor network: a q-learning approachen_US
dc.typeArticleen_US

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