|تعداد مشاهده مقاله||111,633,974|
|تعداد دریافت فایل اصل مقاله||86,254,443|
Hybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks
|Journal of Information Technology Management|
|مقاله 5، دوره 11، شماره 1، 2019، صفحه 76-101 اصل مقاله (1.58 M)|
|نوع مقاله: Research Paper|
|شناسه دیجیتال (DOI): 10.22059/jitm.2019.280639.2354|
|Amirhossein Barzin1؛ Ahmad Sadeghieh* 2؛ Hassan Khademi Zare2؛ Mahboobeh Honarvar3|
|1PhD Candidate, Industrial Engineering, Azadi Pardis of Yazd University, Yazd University, Yazd, Iran.|
|2Professor, Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd., Safayieh, PO Box: 89195-741, Yazd, Iran.|
|3Assistant Professor of Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd., Safayieh, PO Box: 89195-741, Yazd, Iran|
|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.|
|Wireless Sensor Networks؛ Clustering؛ Bio-inspired Algorithm؛ Firefly Algorithm؛ Shuffled Frog Leaping Algorithm|
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