Evasion Paths in Mobile Sensor Networks
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Abstract (arXiv)
Suppose that ball-shaped sensors wander in a bounded domain. A sensor doesn't know its location but does know when it overlaps a nearby sensor. We say that an evasion path exists in this sensor network if a moving intruder can avoid detection. In "Coordinate-free coverage in sensor networks with controlled boundaries via homology", Vin deSilva and Robert Ghrist give a necessary condition, depending only on the time-varying connectivity data of the sensors, for an evasion path to exist. Using zigzag persistent homology, we provide an equivalent condition that moreover can be computed in a streaming fashion. However, no method with time-varying connectivity data as input can give necessary and sufficient conditions for the existence of an evasion path. Indeed, we show that the existence of an evasion path depends not only on the fibrewise homotopy type of the region covered by sensors but also on its embedding in spacetime. For planar sensors that also measure weak rotation and distance information, we provide necessary and sufficient conditions for the existence of an evasion path.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Aug 2013.
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Citing papers per year: 2021: 3; 2022: 1.
4 papers.
- 2021Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecastingcited by 67
- 2022Approximating Persistent Homology for Large Datasetscited by 8
- 2021Topological Information Retrieval with Dilation-Invariant Bottleneck Comparative Measurescited by 2
- 2021A discrete optimisation approach for target path planning whilst evading sensorscited by 0
- 2022Approximating Persistent Homology for Large Datasets19 Apr 2022
- 2021A discrete optimisation approach for target path planning whilst evading sensors16 Jun 2021
- 2021Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting10 May 2021
- 2021Topological Information Retrieval with Dilation-Invariant Bottleneck Comparative Measures4 Apr 2021