Netostat: analyzing dynamic flow patterns in high-speed networks

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, s...

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Bibliographic Details
Published in:Cluster computing 2022-08, Vol.25 (4), p.2915-2930
Main Authors: Murugesan, Sugeerth, Kiran, Mariam, Hamann, Bernd, Weber, Gunther H.
Format: Article
Language:English
Subjects:
Behavior
Clustering
Computer Communication Networks
Computer Science
difference graphs
Flow distribution
graph analysis
Graphs
Load
local clustering algorithm
MATHEMATICS AND COMPUTING
Network analysis
network design
Operating Systems
Processor Architectures
Social network analysis
Social networks
Software
Traffic engineering
Visualization
Wide area networks
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Summary: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.
ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-022-03543-0