Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks
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Affiliation
Wuhan University of Technology, Wuhan, ChinaSouth-Central University for Nationalities, Wuhan, China
University of Derby
Nanyang Technological University, Singapore
Issue Date
2019-10-04
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Data fusion can effectively reduce the amount of data transmission and network energy consumption in wireless sensor networks (WSNs). However the existing data fusion schemes lead to additional delay overhead and power consumptions. In order to improve the performance of WSNs, an intelligent data fusion algorithm based on hybrid delay-aware clustering (HDC) in WSNs is proposed, which combines the advantages of single-layer cluster structure and multi-layer cluster structure, and adaptive selects the clustering patterns of the cluster by the decision function to achieve the tradeoff between network delay and energy consumption. The network model of HDC is presented, and theoretical analysis of the delay and energy consumption of single-layer cluster and multi-layer cluster are provided. And the energy efficient clustering algorithm and the dynamic cluster head re-selection algorithm are proposed to optimize network energy consumption and load balancing of the network. Simulation results show that, compared with the existing delay-aware models, the proposed scheme can effectively reduce the network delay, network energy consumption, and extend the network lifetime simultaneously.Citation
Liu, X., Zhu, R., Anjum, A., Wang, J., Zhang, H. and Ma, M., (2020). 'Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks'. Future Generation Computer Systems, 104, pp. 1-14. DOI: 10.1016/j.future.2019.10.001Publisher
ElsevierJournal
Future Generation Computer SystemsDOI
10.1016/j.future.2019.10.001Type
ArticleLanguage
enISSN
0167-739Xae974a485f413a2113503eed53cd6c53
10.1016/j.future.2019.10.001
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