A novel energy-balanced unequal fuzzy clustering algorithm for 3D wireless sensor networks
Dang Thanh Hai, Nguyen Thi Tam, Lê Hoàng Sơn, Lê Trọng Vĩnh · 2016
In this paper, we consider the problem of designing an efficient topology in 3D Wireless Sensor Network (3D-WSN) that balances node energy consumption, improves efficiency of data transmission and prolongs network lifetime. 3D-WSN has attracted significant interests in recent years due to its applications in various disciplinary fields such as target detection, object tracking, and security surveillance. The proposed method called FCM-PSOEB firstly generates the energy-efficient clusters including cluster heads (CHs) and cluster members (non-CHs) using an improved Fuzzy C-Means algorithm. Then, Particle Swarm Optimization is used to determine optimal CHs for reducing the number of network disconnects from the current clusters. Finally, a new procedure is proposed to assign non-CHs to the most appropriate clusters in order to maintain load balancing between clusters. FCM-PSOEB is empirically validated on real 3D datasets against the relevant protocols such as LEACH, LEACH-C and K-Means. The experimental results demonstrate the efficiency of the proposed method.