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A Density-based Energy-efficient Clustering Heterogeneous Algorithm for Wireless Sensor Networks

Clustering is an efficient method adopted in various routing algorithms for wireless sensor networks. However, most clustering algorithms are not suitable for heterogeneous networks. In this paper, we propose a Density-based Energy-efficient Clustering Heterogeneous Algorithm (DECHA). In DECHA, we define the density of a node and together with its energy condition to adjust the probability for the candidate cluster head selection dynamically. Candidate cluster heads further evaluate the energy level of its neighbors and adjust to find more proper cluster heads. Moreover, we design an intra-cluster algorithm as well as a multi-hop inter-cluster routing algorithm. Simulation results show that cluster heads are properly deployed in a heterogeneous wireless sensor network. Compared with some popular algorithms, in our DECHA, the stability period and network lifetime and prolonged and total energy consumption is prominently reduced.