Topology Inference of Unknown Networks Based on Robust Virtual Coordinate Systems
| Autor: | Chen-Nee Chuah, Taha Bouchoucha, Zhi Ding |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer Networks and Communications
Computer science principal component analysis Distributed computing Inference 020206 networking & telecommunications 02 engineering and technology Network topology Telecommunications network Graph Computer Science Applications Hop (networking) Network connectivity error measurement 0202 electrical engineering electronic engineering information engineering Computer Science::Networking and Internet Architecture Electrical and Electronic Engineering Networking & Telecommunications Distributed Computing Dissemination hop distance Software Virtual coordinate systems |
| Zdroj: | Bouchoucha, Taha; Chuah, Chen-Nee; & Ding, Zhi. (2019). Topology Inference of Unknown Networks Based on Robust Virtual Coordinate Systems. IEEE/ACM Transactions on Networking, 27(1), 405-418. doi: 10.1109/tnet.2018.2888600. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/0qr8v8kg |
| DOI: | 10.1109/tnet.2018.2888600. |
| Popis: | © 2018 IEEE. Learning and exploring the connectivity of unknown networks represent an important problem in practical applications of communication networks and social-media networks. Modeling large-scale networks as connected graphs is highly desirable to extract their connectivity information among nodes to visualize network topology, disseminate data, and improve routing efficiency. This paper investigates a simple measurement model in which a small subset of source nodes collect hop distance information from networked nodes in order to generate a virtual coordinate system (VCS) for networks of unknown topology. We establish the VCS to define logical distance among nodes based on principal component analysis and to determine connectivity relationship and effective routing methods. More importantly, we present a robust analytical algorithm to derive the VCS against practical issues of missing and corrupted measurements. We also develop a connectivity inference method which classifies nodes into layers based on the hop distances and derives partial information on network connectivity. |
| Databáze: | OpenAIRE |
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