An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks

In recent years, Wireless Sensor Networks (WSNs) have benefitted from their integration with Internet of Things (IoT) applications. WSN usage for monitoring and tracing applications shows massive acceleration, whether indoors or outdoors. WSN is constructed from interconnected sensors, limited resou...

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Autores principales:	Mahmoud Moshref, Rizik Al-Sayyed, Saleh Al-Sharaeh
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Quality of service wireless sensor networks multi-objective algorithms clustering scheduling pareto front Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/d6788be180e145bfa1c187fe93de6519
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id	oai:doaj.org-article:d6788be180e145bfa1c187fe93de6519
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spelling	oai:doaj.org-article:d6788be180e145bfa1c187fe93de65192021-11-18T00:07:37ZAn Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks2169-353610.1109/ACCESS.2021.3122526https://doaj.org/article/d6788be180e145bfa1c187fe93de65192021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9585092/https://doaj.org/toc/2169-3536In recent years, Wireless Sensor Networks (WSNs) have benefitted from their integration with Internet of Things (IoT) applications. WSN usage for monitoring and tracing applications shows massive acceleration, whether indoors or outdoors. WSN is constructed from interconnected sensors, limited resource (battery), which requires considerable importance on deployment and routing strategies, to improve the performance of Quality of Service (QoS) in WSNs. Many of the existing strategies are based on metaheuristics algorithms such as Genetic Algorithms to resolve the problem. This research proposes a new algorithm, Enhanced Non-Dominated Sorting Genetic Routing Algorithm (ENSGRA), to improve the QoS in WSNs. The proposed algorithm relies on Non-Dominated Sorting Genetic Algorithm 3 (NSGA-III), but adjusts reference points through the use of a dynamic weighted clustered scheduled vector to obtain new solutions. Moreover, ENSGRA can be used to find an integration between two parents crossover with multi-parent crossover (MPX), to produce multiple children and improve new offspring to obtain the optimal Pareto Fronts (PF). This algorithm excels when compared with the lagged multi-objective jumping particle swarm optimization, Non-dominated Sorting Genetic Algorithm–II and NSGA-III in terms of the QoS model (31% optimization percentage). Results show that the proposed ENSGRA is superior over other algorithms in evaluation measures for multi-objective algorithms.Mahmoud MoshrefRizik Al-SayyedSaleh Al-SharaehIEEEarticleQuality of servicewireless sensor networksmulti-objective algorithmsclusteringschedulingpareto frontElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 149176-149195 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Quality of service wireless sensor networks multi-objective algorithms clustering scheduling pareto front Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Quality of service wireless sensor networks multi-objective algorithms clustering scheduling pareto front Electrical engineering. Electronics. Nuclear engineering TK1-9971 Mahmoud Moshref Rizik Al-Sayyed Saleh Al-Sharaeh An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks
description	In recent years, Wireless Sensor Networks (WSNs) have benefitted from their integration with Internet of Things (IoT) applications. WSN usage for monitoring and tracing applications shows massive acceleration, whether indoors or outdoors. WSN is constructed from interconnected sensors, limited resource (battery), which requires considerable importance on deployment and routing strategies, to improve the performance of Quality of Service (QoS) in WSNs. Many of the existing strategies are based on metaheuristics algorithms such as Genetic Algorithms to resolve the problem. This research proposes a new algorithm, Enhanced Non-Dominated Sorting Genetic Routing Algorithm (ENSGRA), to improve the QoS in WSNs. The proposed algorithm relies on Non-Dominated Sorting Genetic Algorithm 3 (NSGA-III), but adjusts reference points through the use of a dynamic weighted clustered scheduled vector to obtain new solutions. Moreover, ENSGRA can be used to find an integration between two parents crossover with multi-parent crossover (MPX), to produce multiple children and improve new offspring to obtain the optimal Pareto Fronts (PF). This algorithm excels when compared with the lagged multi-objective jumping particle swarm optimization, Non-dominated Sorting Genetic Algorithm–II and NSGA-III in terms of the QoS model (31% optimization percentage). Results show that the proposed ENSGRA is superior over other algorithms in evaluation measures for multi-objective algorithms.
format	article
author	Mahmoud Moshref Rizik Al-Sayyed Saleh Al-Sharaeh
author_facet	Mahmoud Moshref Rizik Al-Sayyed Saleh Al-Sharaeh
author_sort	Mahmoud Moshref
title	An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks
title_short	An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks
title_full	An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks
title_fullStr	An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks
title_full_unstemmed	An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks
title_sort	enhanced multi-objective non-dominated sorting genetic routing algorithm for improving the qos in wireless sensor networks
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/d6788be180e145bfa1c187fe93de6519
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An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks

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