Identifying Neighbor and Connectivity of Wireless Sensor Networks with Poisson Point Process

Identifying neighbor and connectivity are the fundamental requirements in wireless sensor networks. The sensor nodes are scattered randomly over the area of interest and their first step is to identify their immediate neighbors, i.e., the nodes with which they have direct wireless communication. On the other hand, connectivity ensures that sensor nodes can communicate with each other in order to aggregate sensing data hop by hop to the base stations (sink nodes). In this paper, we study identifying neighbor and connectivity in the context of wireless sensor networks, using Poisson point process theory.