@ARTICLE{ iet:/content/journals/10.1049/iet-wss.2016.0115, author = {Jianpo Li}, author = {Xindi Hou}, author = {Dan Su}, author = {Jean De Dieu Munyemana}, keywords = {multiparameter iteration method;wireless sensor network;energy utilisation;data transmission;fuzzy control;transmission power control;base station;energy consumption;fuzzy power-optimised clustering routing algorithm;}, ISSN = {2043-6386}, language = {English}, abstract = {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 , weight of election parameters α = 0.2 , adjustment parameter of cluster radius 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%.}, title = {Fuzzy power-optimised clustering routing algorithm for wireless sensor networks}, journal = {IET Wireless Sensor Systems}, issue = {5}, volume = {7}, year = {2017}, month = {October}, pages = {130-137(7)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=d943qgfcj2rd1.x-iet-live-01content/journals/10.1049/iet-wss.2016.0115} }