An improved fuzzy unequal clustering algorithm for wireless sensor network

This paper proposes a novel energy efficient unequal clustering scheme for large scale wireless sensor networks(WSNs) which aims to balance the node power consumption and prolong the network lifetime as long as possible. Our approach focuses on energy efficient clustering scheme and inter-cluster routing protocol. On the one hand, considering each node´s some local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine one node´s chance of becoming cluster head and estimate the cluster-head radius. On the other hand, the application of Ant Colony Optimization (ACO) to inter-cluster routing constructs energy-aware routing between cluster heads and base station, which reduces the energy consumption of cluster heads and solves the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The confirmation experiment results have indicated the proposed clustering scheme has more superior performance than other methods such as LEACH and EEUC.