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%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.