Growing Connected Networks Under Privacy Constraint: Achieving Trade-Off Between Performance And Security

Abstract

In this paper, we consider the problem of adding links into an undirected connected network. The objective is to achieve a trade-off between maximizing the algebraic connectivity of the resulting network (which defines the convergence speed of the consensus protocol) and minimizing the increase of the largest eigenvalue of its adjacency matrix, namely, maintaining the network to be secured against infection. In addition, the problem needs to be solved under privacy constraint on the network corresponding to the unavailability of the global network topology. To this end, a distributed strategy performed by each nodes and based solely upon their local neighbors information is proposed. The approach is composed of eigenvalue sensitivity analysis and distributed estimation of eigenvectors corresponding to both performance and security metrics. A numerical example is presented to demonstrate and evaluate the proposed strategy.

Publication Date

2-8-2015

Publication Title

Proceedings of the IEEE Conference on Decision and Control

Volume

54rd IEEE Conference on Decision and Control,CDC 2015

Number of Pages

312-317

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/CDC.2015.7402219

Socpus ID

84961999787 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84961999787

This document is currently not available here.

Share

COinS