A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the Internet of Things (IOT)

In this paper, we propose a new constructing approach for a weighted topology of wireless sensor networks (WSNs) based on local-world theory for the Internet of Things (IOT). Based on local-world theory, an uneven clustering weighted evolving model of WSNs is designed. The definitions of edge weight and vertex strength take sensor energy, transmission distance, and flow into consideration. The vertex strengths drive the growth of topology; meanwhile, the edge weights change correspondingly. Experimental data demonstrate that the WSN topology we obtain has the property of weighted networks of the IOT: the edge weight, vertex degree, and strength follow a power-law distribution. Related IOT research work shows that weighted WSNs not only share the robustness and fault tolerance of weight-free networks, but also reduce the probability that successive node breakdowns occur; furthermore, they enhance the synchronization of WSNs.