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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Damage detection via shortest-path network sampling.

Fabio Ciulla¹, Nicola Perra¹, Andrea Baronchelli²

¹Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, Massachusetts 02115, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|October 30, 2014

Summary

This summary is machine-generated.

Shortest-path sampling effectively detects damage in large networked systems. This method accurately identifies damaged nodes, outperforming false positives for precise damage localization.

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Area of Science:

Network Science
Systems Engineering
Data Analysis

Background:

Large networked systems are vulnerable to failures and damages that can disrupt functionality.
Current damage detection methods often rely on sampling strategies with unverified effectiveness.

Purpose of the Study:

To investigate the performance of shortest-path sampling for damage detection in large-scale networks.
To develop and evaluate metrics for assessing network status post-damage.

Main Methods:

Utilized shortest-path sampling to probe network structures.
Defined metrics to characterize network sampling before and after damage.
Applied statistical estimation to determine node status (damaged/not damaged).

Main Results:

The proposed methodology demonstrated flexibility in balancing detection accuracy and sampling probe count.
Testing on synthetic and real network data showed superior identification of damaged nodes over false positives.
The approach precisely uncovered damage in all studied systems.

Conclusions:

Shortest-path sampling is a viable and effective strategy for damage detection in large networks.
The developed metrics and methodology offer a tunable approach for network damage assessment.
This technique enables accurate localization of damage with a low false positive rate.