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Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink

With the advances in sensing technologies, sensor networks became the core of several different networks, including the Internet of Things (IoT) and drone networks. This led to the use of sensor networks in many critical applications including military, health care, and commercial applications. In a...

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Autores principales: El-Fouly, Fatma H., Altamimi, Ahmed B., Ramadan, Rabie A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10004472/
https://www.ncbi.nlm.nih.gov/pubmed/36560153
http://dx.doi.org/10.3390/s22249789
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author El-Fouly, Fatma H.
Altamimi, Ahmed B.
Ramadan, Rabie A.
author_facet El-Fouly, Fatma H.
Altamimi, Ahmed B.
Ramadan, Rabie A.
author_sort El-Fouly, Fatma H.
collection PubMed
description With the advances in sensing technologies, sensor networks became the core of several different networks, including the Internet of Things (IoT) and drone networks. This led to the use of sensor networks in many critical applications including military, health care, and commercial applications. In addition, sensors might be mobile or stationary. Stationary sensors, once deployed, will not move; however, mobile nodes can move from one place to another. In most current applications, mobile sensors are used to collect data from stationary sensors. This raises many energy consumption challenges, including sensor networks’ energy consumption, urgent messages transfer for real-time analysis, and path planning. Moreover, sensors in sensor networks are usually exposed to environmental parameters and left unattended. These issues, up to our knowledge, are not deeply covered in the current research. This paper develops a complete framework to solve these challenges. It introduces novel path planning techniques considering areas’ priority, environmental parameters, and urgent messages. Consequently, a novel energy-efficient and reliable clustering algorithm is proposed considering the residual energy of the sensor nodes, the quality of wireless links, and the distance parameter representing the average intra-cluster distance. Moreover, it proposes a real-time, energy-efficient, reliable and environment-aware routing, taking into account the environmental data, link quality, delay, hop count, nodes’ residual energy, and load balancing. Furthermore, for the benefit of the sensor networks research community, all proposed algorithms are formed in integer linear programming (ILP) for optimal solutions. All proposed techniques are evaluated and compared to six recent algorithms. The results showed that the proposed framework outperforms the recent algorithms.
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spelling pubmed-100044722023-03-11 Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink El-Fouly, Fatma H. Altamimi, Ahmed B. Ramadan, Rabie A. Sensors (Basel) Article With the advances in sensing technologies, sensor networks became the core of several different networks, including the Internet of Things (IoT) and drone networks. This led to the use of sensor networks in many critical applications including military, health care, and commercial applications. In addition, sensors might be mobile or stationary. Stationary sensors, once deployed, will not move; however, mobile nodes can move from one place to another. In most current applications, mobile sensors are used to collect data from stationary sensors. This raises many energy consumption challenges, including sensor networks’ energy consumption, urgent messages transfer for real-time analysis, and path planning. Moreover, sensors in sensor networks are usually exposed to environmental parameters and left unattended. These issues, up to our knowledge, are not deeply covered in the current research. This paper develops a complete framework to solve these challenges. It introduces novel path planning techniques considering areas’ priority, environmental parameters, and urgent messages. Consequently, a novel energy-efficient and reliable clustering algorithm is proposed considering the residual energy of the sensor nodes, the quality of wireless links, and the distance parameter representing the average intra-cluster distance. Moreover, it proposes a real-time, energy-efficient, reliable and environment-aware routing, taking into account the environmental data, link quality, delay, hop count, nodes’ residual energy, and load balancing. Furthermore, for the benefit of the sensor networks research community, all proposed algorithms are formed in integer linear programming (ILP) for optimal solutions. All proposed techniques are evaluated and compared to six recent algorithms. The results showed that the proposed framework outperforms the recent algorithms. MDPI 2022-12-13 /pmc/articles/PMC10004472/ /pubmed/36560153 http://dx.doi.org/10.3390/s22249789 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
El-Fouly, Fatma H.
Altamimi, Ahmed B.
Ramadan, Rabie A.
Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
title Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
title_full Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
title_fullStr Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
title_full_unstemmed Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
title_short Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
title_sort energy and environment-aware path planning in wireless sensor networks with mobile sink
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10004472/
https://www.ncbi.nlm.nih.gov/pubmed/36560153
http://dx.doi.org/10.3390/s22249789
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