Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks
In order to achieve the sensing, communication and processing tasks of Wireless Sensor Networks, an energy-efficient routing protocol is required to manage the dissipated energy of the network and to minimalize the traffic and the overhead during the data transmission stages. Clustering is the most...
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doaj-3a6d460df7bd4baaa830fb41201e10c12020-11-25T00:11:17ZfasUniversity of TehranJournal of Information Technology Management 2008-58932423-50592019-01-011117610110.22059/jitm.2019.280639.235473274Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor NetworksAmirhossein Barzin0Ahmad Sadeghieh1Hassan Khademi Zare2Mahboobeh Honarvar3PhD Candidate, Industrial Engineering, Azadi Pardis of Yazd University, Yazd University, Yazd, Iran.Professor, Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd., Safayieh, PO Box: 89195-741, Yazd, Iran.Professor, Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd., Safayieh, PO Box: 89195-741, Yazd, Iran.Assistant Professor of Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd., Safayieh, PO Box: 89195-741, Yazd, IranIn order to achieve the sensing, communication and processing tasks of Wireless Sensor Networks, an energy-efficient routing protocol is required to manage the dissipated energy of the network and to minimalize the traffic and the overhead during the data transmission stages. Clustering is the most common technique to balance energy consumption amongst all sensor nodes throughout the network. In this paper, a multi-objective bio-inspired algorithm based on the Firefly and the Shuffled frog-leaping algorithms is presented as a clustering-based routing protocol for Wireless Sensor Networks. The multi-objective fitness function of the proposed algorithm has been performed on different criteria such as residual energy of nodes, inter-cluster distances, cluster head distances to the sink and overlaps of clusters, to select the proper cluster heads at each round. The parameters of the proposed approach in the clustering phase can be adaptively tuned to achieve the best performance based on the network requirements. Simulation outcomes have displayed average lifetime improvements of up to 33.95%, 32.62%, 12.1%, 13.85% compared with LEACH, ERA, SIF and FSFLA respectively, in different network scenarios.https://jitm.ut.ac.ir/article_73274_14bdd0f20bb4cf57904ddcc56d18fee0.pdfwireless sensor networksclusteringbio-inspired algorithmfirefly algorithmshuffled frog leaping algorithm |
collection |
DOAJ |
language |
fas |
format |
Article |
sources |
DOAJ |
author |
Amirhossein Barzin Ahmad Sadeghieh Hassan Khademi Zare Mahboobeh Honarvar |
spellingShingle |
Amirhossein Barzin Ahmad Sadeghieh Hassan Khademi Zare Mahboobeh Honarvar Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks Journal of Information Technology Management wireless sensor networks clustering bio-inspired algorithm firefly algorithm shuffled frog leaping algorithm |
author_facet |
Amirhossein Barzin Ahmad Sadeghieh Hassan Khademi Zare Mahboobeh Honarvar |
author_sort |
Amirhossein Barzin |
title |
Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks |
title_short |
Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks |
title_full |
Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks |
title_fullStr |
Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks |
title_full_unstemmed |
Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks |
title_sort |
hybrid bio-inspired clustering algorithm for energy efficient wireless sensor networks |
publisher |
University of Tehran |
series |
Journal of Information Technology Management |
issn |
2008-5893 2423-5059 |
publishDate |
2019-01-01 |
description |
In order to achieve the sensing, communication and processing tasks of Wireless Sensor Networks, an energy-efficient routing protocol is required to manage the dissipated energy of the network and to minimalize the traffic and the overhead during the data transmission stages. Clustering is the most common technique to balance energy consumption amongst all sensor nodes throughout the network. In this paper, a multi-objective bio-inspired algorithm based on the Firefly and the Shuffled frog-leaping algorithms is presented as a clustering-based routing protocol for Wireless Sensor Networks. The multi-objective fitness function of the proposed algorithm has been performed on different criteria such as residual energy of nodes, inter-cluster distances, cluster head distances to the sink and overlaps of clusters, to select the proper cluster heads at each round. The parameters of the proposed approach in the clustering phase can be adaptively tuned to achieve the best performance based on the network requirements. Simulation outcomes have displayed average lifetime improvements of up to 33.95%, 32.62%, 12.1%, 13.85% compared with LEACH, ERA, SIF and FSFLA respectively, in different network scenarios. |
topic |
wireless sensor networks clustering bio-inspired algorithm firefly algorithm shuffled frog leaping algorithm |
url |
https://jitm.ut.ac.ir/article_73274_14bdd0f20bb4cf57904ddcc56d18fee0.pdf |
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