Energy efficient medium access control protocol for data collection in wireless sensor network: a q-learning approach
Yükleniyor...
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In 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.
Açıklama
Anahtar Kelimeler
Internet of Things, MAC Protocols, Q-learning, Scheduling Algorithm, Wireless Sensor Networks
Kaynak
Sustainable Energy Technologies and Assessments
WoS Q Değeri
Q2
Scopus Q Değeri
N/A
Cilt
53
Sayı
Künye
Sah, 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.2022.102530
