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Interactive Investigation of Traffic Congestion on Fat‐Tree Networks Using T ree S cope
Author(s) -
Bhatia H.,
Jain N.,
Bhatele A.,
Livnat Y.,
Domke J.,
Pascucci V.,
Bremer P.T.
Publication year - 2018
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.13442
Subject(s) - computer science , computer network , network topology , visualization , distributed computing , network traffic control , tree (set theory) , data mining , network packet , mathematical analysis , mathematics
Parallel simulation codes often suffer from performance bottlenecks due to network congestion, leaving millions of dollars of investments underutilized. Given a network topology, it is critical to understand how different applications, job placements, routing schemes, etc., are affected by and contribute to network congestion, especially for large and complex networks. Understanding and optimizing communication on large‐scale networks is an active area of research. Domain experts often use exploratory tools to develop both intuitive and formal metrics for network health and performance. This paper presents T ree S cope , an interactive, web‐based visualization tool for exploring network traffic on large‐scale fat‐tree networks. T ree S cope encodes the network topology using a tailored matrix‐based representation and provides detailed visualization of all traffic in the network. We report on the design process of T ree S cope , which has been received positively by network researchers as well as system administrators. Through case studies of real and simulated data, we demonstrate how T ree S cope 's visual design and interactive support for complex queries on network traffic can provide experts with new insights into the occurrences and causes of congestion in the network.