A Local World Evolving Model for Energy-Constrained Wireless Sensor Networks

Energy efficiency is one of the basic requirements of wireless sensor networks (WSNs) yet this problem has not been sufficiently explored in the context of cluster-based sensor networks. Specifically, the interaction of different types of sensor nodes is one of the major factors of energy efficiency in large-scale heterogeneous networks. In this paper, we aim at improving the interactions among sensor nodes, and we present a heterogeneous local-world model to form large-scale wireless sensor networks based on complex network theory. Two types of nodes, normal nodes and cluster nodes, are added to the networks. The degree distribution for this model is obtained analytically by mean-field theory. This approach depicts the evolution of the network as having a topological feature that is not completely exponential and not completely power law; instead, it behaves between them. The experiment and simulation indicate that the control method has excellent robustness and a satisfactory control effect (interaction of different types of sensor nodes). Furthermore, the results also show that the higher the generation rate of the cluster nodes is, the closer the degree distribution follows the power-law distribution.