Accuracy of Homology based Coverage Hole Detection for Wireless Sensor Networks on Sphere

TL;DR

This paper evaluates the accuracy of homology-based methods for detecting coverage holes in wireless sensor networks on spheres, highlighting cases where Rips complex may fail and deriving bounds for detection accuracy.

Contribution

It introduces a new metric for accuracy of coverage hole detection on spheres and provides analytical bounds validated by simulations.

Findings

Rips complex may miss some coverage holes in certain scenarios.

Derived bounds for detection accuracy are consistent with simulation results.

Sphere radius has minimal impact on detection accuracy when large compared to sensor radii.

Abstract

Homology theory has attracted great attention because it can provide novel and powerful solutions to address coverage problems in wireless sensor networks. They usually use an easily computable algebraic object, Rips complex, to detect coverage holes. But Rips complex may miss some coverage holes in some cases. In this paper, we investigate homology-based coverage hole detection for wireless sensor networks on sphere. The situations when Rips complex may miss coverage holes are first presented. Then we choose the proportion of the area of coverage holes missed by Rips complex as a metric to evaluate the accuracy of homology-based coverage hole detection approaches. Three different cases are considered for the computation of accuracy. For each case, closed-form expressions for lower and upper bounds of the accuracy are derived. Simulation results are well consistent with the analytical lower and upper bounds, with maximum differences of 0.5% and 3% respectively. Furthermore, it is shown that the radius of sphere has little impact on the accuracy if it is much larger than communication and sensing radii of each sensor.