Localized Algorithm for Precise Boundary Detection in 3D Wireless Networks

Abstract

This research focuses on distributed and localized algorithms for precise boundary detection in 3D wireless networks. Our objectives are in two folds. First, we aim to identify the nodes on the boundaries of a 3D network, which serve as a key attribute that characterizes the network, especially in such geographic exploration tasks as terrain and underwater reconnaissance. Second, we construct locally planarized 2-manifold surfaces for inner and outer boundaries, in order to enable available graph theory tools to be applied on 3D surfaces, such as embedding, localization, partition, and greedy routing among many others. To achieve the first objective, we propose a Unit Ball Fitting (UBF) algorithm that discovers a set of potential boundary nodes, followed by a refinement algorithm, named Isolated Fragment Filtering (IFF), which removes isolated nodes that are misinterpreted as boundary nodes by UBF. Based on the identified boundary nodes, we develop an algorithm that constructs a locally planarized triangular mesh surface for each 3D boundary. Our proposed scheme is localized, requiring information within one-hop neighborhood only. Our simulation results demonstrate that the proposed algorithms can effectively identify boundary nodes and surfaces, even under high measurement errors. As far as we know, this is the first work for discovering boundary nodes and constructing boundary surfaces in 3D wireless networks.

Boundary Detection in 2-D and 3-D Wireless Sensor Networks

“…An event sensor declares itself on the event boundary if it has non-event sensors in its neighbourhood. While the basic idea appears straightforward, event boundary detection is challenging, due to limited sampling density, noisy sensor readings, lossy data delivery, and low computation power of individual sensors [13], [14], calling for efficient information processing and modeling techniques to analyze sensor data, in order to estimate the boundary of events [13]- [17]. The detection of network boundary is to locate the outmost nodes in a sensor network, irrespective of sensor data or events.…”

Deterministic Greedy Routing with Guaranteed Delivery in 3D Wireless Sensor Networks

“…Here, we have assumed that no degenerated edges or nodes exist in the network, and any internal hole (as small as a unit cube) has been identified by [29] to ensure the successful establishment of the UTC mesh. Moreover, we assume a node can create a local coordinates system by using local distance information estimated via standard methods [30].…”

Actor positioning based on molecular geometry in aerial sensor networks

“…Alam and Haas [4] argue that space filling polyhedrons would be more suitable to use for 3D coverage and try to fill the 3D application space with the least number of polyhedrons for maximal coverage. Zhou et al [5] present two algorithms for discovering boundary nodes and constructing boundary surfaces in 3D wireless networks. Bai et al [6] designed and proved the optimality of one and two connectivity patterns under any value of the ratio of communication range over sensing range, among regular lattice deployment patterns.…”