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Collaborative Network Monitoring by Means of Laplacian Spectrum Estimation and Average Consensus

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This paper concerns collaborative monitoring of the robustness of networks partitioned into sub-networks. We consider the critical threshold of a network and the effective graph resistance (Kirchhoff index) of a… Click to show full abstract

This paper concerns collaborative monitoring of the robustness of networks partitioned into sub-networks. We consider the critical threshold of a network and the effective graph resistance (Kirchhoff index) of a sub-graph characterizing the interconnection of sub-networks, that are partitioned from the given network as robustness metric. In which, the critical threshold depends only on the two first moments of the degree distribution while the Kirchhoff index can be computed with Laplacian eigenvalues. Therefore, we show how to estimate jointly the Laplacian eigenvalues and the two first moments of the degree distribution in a distributed way.

Keywords: monitoring; collaborative network; means laplacian; network monitoring; monitoring means; network

Journal Title: International Journal of Control, Automation and Systems
Year Published: 2019

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