Clustering Routing Protocol for WSNs Based on Neural Network Optimization by Improved Firefly Algorithm

doi:10.13190/j.jbupt.2019-161

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (3): 131-137.doi: 10.13190/j.jbupt.2019-161

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Clustering Routing Protocol for WSNs Based on Neural Network Optimization by Improved Firefly Algorithm

DAI Jian-yong^1,2, DENG Xian-hong¹, WANG Bin¹, WANG Heng-hao¹

1. School of Resources, Environment and Safety Engineering, University of South China, Hengyang 421001, China;
2. Hunan Province Engineering Technology Research Center of Uranium Tailings Treatment Technology, Hengyang 421001, China

Received:2019-07-14 Online:2020-06-28 Published:2020-06-24
Supported by:

Abstract

Abstract: Aiming at solving the problem of uneven energy consumption in wireless sensor networks (WSNs),an uneven clustering routing protocol based on the improved firefly algorithm optimized back propagation(BP) neural network (IFABPUC) is proposed. To balance the intra-cluster load and reduce the inter-cluster communication distances,a weighting factor which takes into account four more evaluation indexes than the conventional firefly algorithm is embedded in the improved firefly algorithm. To achieve the best clustering, BP neural network is combined to optimize the way to path selection and cluster head election. Simulations show that IFABPUC can effectively extend the lifecycle of networks,save energy and balance energy consumption.

Key words: back propagation neural network, firefly algorithm, uneven clustering

CLC Number:

TP393

DAI Jian-yong, DENG Xian-hong, WANG Bin, WANG Heng-hao. Clustering Routing Protocol for WSNs Based on Neural Network Optimization by Improved Firefly Algorithm[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(3): 131-137.

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Clustering Routing Protocol for WSNs Based on Neural Network Optimization by Improved Firefly Algorithm

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