Open AccessOptimised routing and compressive sensing based data communication in wireless sensor network
Author(s) -
Pasupuleti Venkat Rao,
Balaswamy Chinthaguntla
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0130
Subject(s) - throughput , computer science , wireless sensor network , compressed sensing , kronecker delta , energy (signal processing) , multipath propagation , transmission (telecommunications) , algorithm , routing (electronic design automation) , real time computing , data transmission , wireless , computer network , mathematics , telecommunications , channel (broadcasting) , statistics , quantum mechanics , physics
Wireless sensor networks (WSNs) play a prominent role in real‐time applications, like traffic monitoring, tracking the intruder, and so on, which are duly based on the destination. Compressive sensing tracks a wide application in tracking the location, and this study uses the Kronecker basis representation‐based tensor completion (KBR‐TC) model for availing the data communication in WSNs. Additionally, this study proposes a fractional earthworm optimisation (FEWO) algorithm for finding the optimal cluster heads (CHs) in the network. Once the CHs are selected, the multipath is optimally finalised using the fit factor that depends on the energy, trust, distance and delay. The proposed FEWO is designed by modifying standard earthworm algorithm (EWA) with the fractional concept. Finally, the data is compressed using the KBR‐TC model, for data transmission, and the data is sent to the destination, where the data is reconstructed. The analysis of the methods based on energy (J), throughput (%) and delay (ms) reveal that the proposed FEWO method outperformed the existing methods with the maximal energy, throughput and minimal delay of 0.1295 J, 0.1295 J and 88.5768%, respectively.