—This paper discusses the parallelism between the concept of network identifiability introduced by Boolean Net- work Tomography (BNT), and the theory of separating systems, highlighting applications of interest to research in networking. This work evidences how recent results of BNT have direct implications to the formulation of new bounds to the size of separating systems over finite sets. Grounding on these theoretical results, we provide an efficient algorithm for the design of separating systems that meet the bound tightly. We extend the proposed results, bounds and algorithm, to networking appli- cations, including network failure assessment, robust network design and compressed sensing.

Network Identifiability: Advances in Separating Systems and Networking Applications / Bartolini, Novella; Arrigoni, Viviana. - In: IEEE NETWORKING LETTERS. - ISSN 2576-3156. - (2022), pp. 1-1. [10.1109/LNET.2022.3200002]

Network Identifiability: Advances in Separating Systems and Networking Applications

Novella Bartolini;Viviana Arrigoni
2022

Abstract

—This paper discusses the parallelism between the concept of network identifiability introduced by Boolean Net- work Tomography (BNT), and the theory of separating systems, highlighting applications of interest to research in networking. This work evidences how recent results of BNT have direct implications to the formulation of new bounds to the size of separating systems over finite sets. Grounding on these theoretical results, we provide an efficient algorithm for the design of separating systems that meet the bound tightly. We extend the proposed results, bounds and algorithm, to networking appli- cations, including network failure assessment, robust network design and compressed sensing.
2022
Network Tomography, compressed sensing
01 Pubblicazione su rivista::01a Articolo in rivista
Network Identifiability: Advances in Separating Systems and Networking Applications / Bartolini, Novella; Arrigoni, Viviana. - In: IEEE NETWORKING LETTERS. - ISSN 2576-3156. - (2022), pp. 1-1. [10.1109/LNET.2022.3200002]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1656958
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