Inferring link changes in dynamic networks through power spectral density variations

John A.W.B. Costanzo, Donatello Materassi, Bruno Sinopoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, we present a computationally efficient method of detecting and localizing changes in the dynamics of links in networks of LTI systems, represented as a collection of interdependent time series. We define 'link' to mean a dependence of one node process on another. Our method uses only passively obtained second-order statistics. The dynamics of the network are not required to be known. As such, we do not require a least-squares step to find system parameters, nor do we risk using possibly corrupted data to update what we believe is the original system model. As a passive method, it does not require injecting control signals or manipulating the network. The corrupted link is only partially identified, but the scope of the problem is narrowed significantly. We detect a link change by tracking the cross power spectral density between each pair of node processes in the network. When a link changes, many pairs of nodes will experience a change in their power spectral density; we call these 'changed pairs'. We characterize which pairs of nodes in the network will change depending on which link changes. We use this characterization to uniquely find the strongly connected component containing the head of the changed link. We also provide a characterization of when the tail of the changed link can be uniquely identified.

Original languageEnglish (US)
Title of host publication55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages220-227
Number of pages8
ISBN (Electronic)9781538632666
DOIs
StatePublished - Jul 1 2017
Externally publishedYes
Event55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017 - Monticello, United States
Duration: Oct 3 2017Oct 6 2017

Publication series

Name55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
Volume2018-January

Other

Other55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
Country/TerritoryUnited States
CityMonticello
Period10/3/1710/6/17

Bibliographical note

Funding Information:
*This material is based upon work partially supported by the National Science Foundation under grants no. 1646526 and no. 1638327. *D. Materassi is supported in part by NSF grant CNS-1553504. 1J. Costanzo & B. Sinopoli are with the department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15237, USA [email protected], [email protected] 2D. Materassi is with the department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA [email protected]

Funding Information:
This material is based upon work partially supported by the National Science Foundation under grants no. 1646526

Publisher Copyright:
© 2017 IEEE.

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