Energy-Efficient Design of MI Communication-Based 3-D Non-Conventional WSNs; IEEE Systems Journal; Vol. 14, iss. 2

Մատենագիտական մանրամասներ
Parent link:IEEE Systems Journal
Vol. 14, iss. 2.— 2020.— [P. 2585-2588]
Համատեղ հեղինակ: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники
Այլ հեղինակներ: Yadav S. Sadanand, Kumar V. Vinay, Dhok S. B. Sanjay, Dzhayakodi Arachshiladzh D. N. K. Dushanta Nalin Kumara
Ամփոփում:Title screen
This paper proposes optimal clustering (OC) for magnetic induction (MI) communication-based 3-D Non-Conventional Wireless Sensor Networks (3-D Non-Conv WSNs) leveraging compressive sensing (CS) and principal component analysis (PCA) with and without consideration of relay node. These WSNs are resource constrained with limited energy reserves. OC for 3-D media is performed using analytical modeling to minimize the energy consumption in the network. Clustering efficacy is further improved by applying the CS and PCA data compression techniques. The performance of the proposed model is evaluated in terms of energy efficiency and network lifetime for three different media (viz., sea water, dry soil, and sedimentary wet rock) by considering three different positions of base station (BS) (viz., center, lateral mid point, and outside of sensing held). Furthermore, from the results, we observed that our proposed techniques save energy up to 84.37% for all base station (BS) positions.
Режим доступа: по договору с организацией-держателем ресурса
Լեզու:անգլերեն
Հրապարակվել է: 2020
Խորագրեր:
Առցանց հասանելիություն:https://doi.org/10.1109/JSYST.2019.2918184
Ձևաչափ: Էլեկտրոնային Գրքի գլուխ
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663718

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330 |a This paper proposes optimal clustering (OC) for magnetic induction (MI) communication-based 3-D Non-Conventional Wireless Sensor Networks (3-D Non-Conv WSNs) leveraging compressive sensing (CS) and principal component analysis (PCA) with and without consideration of relay node. These WSNs are resource constrained with limited energy reserves. OC for 3-D media is performed using analytical modeling to minimize the energy consumption in the network. Clustering efficacy is further improved by applying the CS and PCA data compression techniques. The performance of the proposed model is evaluated in terms of energy efficiency and network lifetime for three different media (viz., sea water, dry soil, and sedimentary wet rock) by considering three different positions of base station (BS) (viz., center, lateral mid point, and outside of sensing held). Furthermore, from the results, we observed that our proposed techniques save energy up to 84.37% for all base station (BS) positions. 
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