Abstract

Coverage is a fundamental problem in wireless sensor networks (WSNs). Conventional studies on this topic focus on 2D ideal plane coverage and 3D full space coverage. The 3D surface of a field of interest (FoI) is complex in many real-world applications. However, existing coverage studies do not produce practical results. In this paper, we propose a new coverage model called surface coverage. In surface coverage, the field of interest is a complex surface in 3D space and sensors can be deployed only on the surface. We show that existing 2D plane coverage is merely a special case of surface coverage. Simulations point out that existing sensor deployment schemes for a 2D plane cannot be directly applied to surface coverage cases. Thus, we target two problems assuming cases of surface coverage to be true. One, under stochastic deployment, what is the expected coverage ratio when a number of sensors are adopted? Two, if sensor deployment can be planned, what is the optimal deployment strategy with guaranteed full coverage with the least number of sensors? We show that the latter problem is NP-complete and propose three approximation algorithms. We further prove that these algorithms have a provable approximation ratio. We also conduct extensive simulations to evaluate the performance of the proposed algorithms.

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