Multiple hole detection in wireless underground sensor networks

Kaushik, Abhinesh

doi:10.1201/9780429444272-25

Cited by 3 publications

(2 citation statements)

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“…Kaushik [9] proposed location-based algorithms to find the boundary nodes and for the detection of holes in WUSNs. The author used the Voronoi diagram to find boundary nodes.…”

Section: Related Workmentioning

confidence: 99%

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Energy-Efficient Deterministic Approach for Coverage Hole Detection in Wireless Underground Sensor Network: Mathematical Model and Simulation

Sharma

Singh

2022

Computers

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Wireless underground sensor networks (WUSNs) are being used in agricultural applications, in border patrol, and in the monitoring of remote areas. Coverage holes in WUSNs are an issue which needs to be dealt with. Coverage holes may occur due to random deployment of nodes as well as the failure of nodes with time. In this paper, a mathematical approach for hole detection using Delaunay geometry is proposed which divides the network region into Delaunay triangles and applies the laws of triangles to identify coverage holes. WUSNs comprise static nodes, and replacing underground nodes is a complex task. A simplistic algorithm for detecting coverage holes in static WSNs/WUSNs is proposed. The algorithm was simulated in the region of interest for the initially randomly deployed network and after energy depletion of the nodes with time. The performance of the algorithm was evaluated by varying the number of nodes and the sensing radius of the nodes. Our scheme is advantageous over other schemes in the following aspects: (1) it builds a mathematical model and polynomial-time algorithm for detecting holes, and (2) the scheme does not work on centralized computation and therefore provides better scalability, (3) is energy-efficient, and (4) provides a cost-effective solution to detect holes with great accuracy and a low detection time. The algorithm takes less than 0.1 milliseconds to detect holes in a 100 m × 100 m-size network with 100 sensor nodes having a sensing radius of 8 m. The detection time shows only a linear change with an increase in the number of nodes in the network, which makes the algorithm applicable for every network size from small to large.

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“…Kaushik [9] proposed location-based algorithms to find the boundary nodes and for the detection of holes in WUSNs. The author used the Voronoi diagram to find boundary nodes.…”

Section: Related Workmentioning

confidence: 99%

“…Besides the potential usage of WUSNs, there are many issues which need to be dealt with. The hole problem [9] is one of the major issues which WUSNs face.…”

Section: Introductionmentioning

confidence: 99%