Cargando…

rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks

In this paper, a new system entropy measure is used to optimize the routing algorithm in power consumption. We introduce the system entropy measure into the problem of industrial wireless sensor networks (iWSNs) routing and propose a high-performance routing algorithm guided by the system entropy me...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiong, Xiaoxiong, Dong, Chao, Niu, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654926/
https://www.ncbi.nlm.nih.gov/pubmed/36365989
http://dx.doi.org/10.3390/s22218291
_version_ 1784829057756561408
author Xiong, Xiaoxiong
Dong, Chao
Niu, Kai
author_facet Xiong, Xiaoxiong
Dong, Chao
Niu, Kai
author_sort Xiong, Xiaoxiong
collection PubMed
description In this paper, a new system entropy measure is used to optimize the routing algorithm in power consumption. We introduce the system entropy measure into the problem of industrial wireless sensor networks (iWSNs) routing and propose a high-performance routing algorithm guided by the system entropy measure (rSEM). Based on the cluster iWSNs architecture, the rSEM selects the cluster heads and cluster member nodes successively, according to the system entropy measure, and constructs the iWSNs with the minimum system entropy. The method of the cluster head selection is traversal, while the method of the cluster member selection is a greedy algorithm to reduce the complexity. The experiments show that the power consumption of the iWSNs generated by the rSEM is in the same order of magnitude as that of Dijkstra in both 2D and 3D scenarios. In addition, the delay of the rSEM is slightly higher than that of LEACH. Therefore, the rSEM is suitable for networks that are sensitive to both the delay and power consumption. The rSEM puts forward a new idea for the design of routing for the next-generation iWSNs, which improves the overall network performance according to the network topology, instead of relying on the power consumption or delay performance only.
format Online
Article
Text
id pubmed-9654926
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-96549262022-11-15 rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks Xiong, Xiaoxiong Dong, Chao Niu, Kai Sensors (Basel) Article In this paper, a new system entropy measure is used to optimize the routing algorithm in power consumption. We introduce the system entropy measure into the problem of industrial wireless sensor networks (iWSNs) routing and propose a high-performance routing algorithm guided by the system entropy measure (rSEM). Based on the cluster iWSNs architecture, the rSEM selects the cluster heads and cluster member nodes successively, according to the system entropy measure, and constructs the iWSNs with the minimum system entropy. The method of the cluster head selection is traversal, while the method of the cluster member selection is a greedy algorithm to reduce the complexity. The experiments show that the power consumption of the iWSNs generated by the rSEM is in the same order of magnitude as that of Dijkstra in both 2D and 3D scenarios. In addition, the delay of the rSEM is slightly higher than that of LEACH. Therefore, the rSEM is suitable for networks that are sensitive to both the delay and power consumption. The rSEM puts forward a new idea for the design of routing for the next-generation iWSNs, which improves the overall network performance according to the network topology, instead of relying on the power consumption or delay performance only. MDPI 2022-10-29 /pmc/articles/PMC9654926/ /pubmed/36365989 http://dx.doi.org/10.3390/s22218291 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiong, Xiaoxiong
Dong, Chao
Niu, Kai
rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks
title rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks
title_full rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks
title_fullStr rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks
title_full_unstemmed rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks
title_short rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks
title_sort rsem: system-entropy-measure-guided routing algorithm for industrial wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654926/
https://www.ncbi.nlm.nih.gov/pubmed/36365989
http://dx.doi.org/10.3390/s22218291
work_keys_str_mv AT xiongxiaoxiong rsemsystementropymeasureguidedroutingalgorithmforindustrialwirelesssensornetworks
AT dongchao rsemsystementropymeasureguidedroutingalgorithmforindustrialwirelesssensornetworks
AT niukai rsemsystementropymeasureguidedroutingalgorithmforindustrialwirelesssensornetworks