SNP: A 1-Manifold Skeleton-Based Navigation Protocol in 3D Sensor Networks

Abstract

We consider the navigation application of 3D sensor networks that can proactively guide the movement of internal users from potential dangers to a safe exit, where a 3D sensor network serves as a reactive system, instead of a monitoring tool or a medium of data acquisition. Most if not all existing efforts in this line concentrate on 2D cases only, and none of them can be readily applied to 3D sensor networks, posing it a non-trivial challenge to design an effective and light-weight navigation protocol in 3D sensor networks. In this paper, we propose the first location-free, distributed, and scalable navigation protocol that can provide a navigation route for users inside the 3D sensor network with guaranteed safety. More specifically, we formulate the navigation problem as the minimum cumulative exposure problem, and design SNP, a navigation protocol based on the so-called 1-manifold skeleton, which offers a safe path with a near-optimal cumulative exposure to dangers. Extensive simulations validate the effectiveness and efficiency of the proposed algorithm.