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Netostat: analyzing dynamic flow patterns in high-speed networks.

Authors :
Murugesan, Sugeerth
Kiran, Mariam
Hamann, Bernd
Weber, Gunther H.
Source :
Cluster Computing. Aug2022, Vol. 25 Issue 4, p2915-2930. 16p.
Publication Year :
2022

Abstract

Understanding flow traffic patterns in networks, such as the Internet or service provider networks, is crucial to improving their design and building them robustly. However, as networks grow and become more complex, it is increasingly cumbersome and challenging to study how the many flow patterns, sizes and the continually changing source-destination pairs in the network evolve with time. We present Netostat, a visualization-based network analysis tool that uses visual representation and a mathematics framework to study and capture flow patterns, using graph theoretical methods such as clustering, similarity and difference measures. Netostat generates an interactive graph of all traffic patterns in the network, to isolate key elements that can provide insights for traffic engineering. We present results for U.S. and European research networks, ESnet and GEANT, demonstrating network state changes, to identify major flow trends, potential points of failure, and bottlenecks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13867857
Volume :
25
Issue :
4
Database :
Academic Search Index
Journal :
Cluster Computing
Publication Type :
Academic Journal
Accession number :
157987846
Full Text :
https://doi.org/10.1007/s10586-022-03543-0