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Issue title: Special Section: Applications of intelligent & fuzzy theory in engineering technologies and applied science
Guest editors: Stanley Lima and Álvaro Rocha
Article type: Research Article
Authors: Xu, Binga | Liu, Liqunb; * | Zhang, Xiaopingc | Wu, Xianjund
Affiliations: [a] School of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming, China | [b] School of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, China | [c] School of Mathematics and Statistics, The University of Sheffield, Sheffield, UK | [d] School of Computing Center, Guangdong University of Petrochemical Technology, Maoming, China
Correspondence: [*] Corresponding author. Liqun Liu, School of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, China. E-mail: [email protected]
Abstract: In order to effectively improve the data transmission efficiency of wireless sensor networks (WSN), a new wireless sensor network chain routing algorithm is proposed based on adaptive backoff-adjusted medium access control. At first, the optimal transmission back-off time of undetermined frames is estimated by the number of active nodes in this algorithm, and the performance evaluation index of WSN is presented with area coverage, transmission distance and residual energy. At the same time, the number of collisions and transmission attempt rate are given with adaptive backoff-adjusted medium access control, and the chain routing algorithm is build. Finally, the key factors influencing the algorithm are deeply studied through experimental platform and numerical simulation with MATLAB. The results show that, compared with the traditional chain routing algorithm and progressive best backoff algorithm, the algorithm has great advantages in terms of chaining efficiency, node life cycle and delay.
Keywords: Wireless sensor network, chain routing, energy, chaining, life cycle
DOI: 10.3233/JIFS-169658
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 3035-3041, 2018
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