Fuzzy power-optimised clustering routing algorithm for wireless sensor networks

Transmission power control is an effective method to reduce energy consumption for wireless sensor networks. However, the current algorithms of power control have relatively low accuracy. At the same time, the parameters cannot be adjusted dynamically. In order to improve the energy utilisation as w...

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Bibliographic Details
Published in:IET wireless sensor systems 2017-10, Vol.7 (5), p.130-137
Main Authors: Li, Jianpo, Hou, Xindi, Su, Dan, Munyemana, Jean De Dieu
Format: Article
Language:English
Subjects:
base station
data transmission
energy consumption
energy utilisation
fuzzy control
fuzzy power‐optimised clustering routing algorithm
iterative methods
multiparameter iteration method
pattern clustering
power control
Research Article
telecommunication control
telecommunication network routing
transmission power control
wireless sensor network
wireless sensor networks
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Summary:Transmission power control is an effective method to reduce energy consumption for wireless sensor networks. However, the current algorithms of power control have relatively low accuracy. At the same time, the parameters cannot be adjusted dynamically. In order to improve the energy utilisation as well as data transmission efficiency and balance the load, therefore, a fuzzy power-optimised clustering routing algorithm is proposed in this study. The algorithm optimises the iteration radius and classifies the sensor nodes into different categories according to their node degree. Then select the cluster head by multi-parameter iteration adaptively among the same category, and optimise the cluster structure with a comprehensive consideration of parameters such as degree of centralisation, distance between node and base station and so on. Finally, fuzzy control is used to adjust the transmission power of cluster nodes dynamically to minimise the energy consumption. Simulation results show that when the average cluster radius $R_L = 60$RL=60, weight of election parameters $\alpha = 0.2$α=0.2, adjustment parameter of cluster radius $\eta = 0.7$η=0.7, compared with other similar algorithms, the proposed algorithm prolongs the lifetime by at least 42.2% and increases the amount of data packets by at least 40.1%.
ISSN:2043-6386
2043-6394
2043-6394
DOI:10.1049/iet-wss.2016.0115