Optimal density estimation for exposure-path prevention in wireless sensor networks using percolation theory

Most existing works on sensor coverage mainly concentrate on the full coverage models which ensure that all points in the deployment region are covered at the expense of high complexity and cost. In contrast, the exposure-path prevention does not require full coverage sensor deployment, and instead it only needs the partial coverage, because the exposure paths are prevented as long as no moving objects or phenomena can go through a deployment region without being detected. Towards this end, we focus on the partial coverage by applying the percolation theory to solve the exposure path problem for wireless sensor networks. Specifically, we propose a bond-percolation based scheme by mapping the exposure path problem into a bond percolation model. Using this model, we derive the analytical expressions of critical densities for wireless sensor networks under random sensor deployment.