Analyzing Connectivity Outcomes in WSNs with Gaussian Deployment Patterns

Ensuring optimal connectivity in a Wireless Sensor Network (WSN) is a paramount. This network characteristic is influenced by several factors, such as communication range, propagation model, and deployment strategy. The Gaussian deployment distribution is often utilized to approximate the nature of random deployments, particularly when the WSN is organized into clusters that are nested within each other. This approach is advantageous for aligning with the inherent randomness and spatial characteristics of such deployments. This paper delves into the impact of Gaussian deployment on WSN connectivity, focusing on how this clustering and nesting influence connectivity, with the goal of identifying the most effective strategies for maximizing connectivity probability.