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- W2578400154 abstract "Diversity, dynamicity, and the huge volume of traffic in the network between datacenters has risen network administrators concerns on how to efficiently visualize their system in real-time. To deal with these challenges, we present in this paper a visualization framework based on advanced machine learning, traffic characterization, sampling, and graphical visualization algorithms, which aims to efficiently support inter-datacenter network monitoring. Experimental results show the framework is able to process real-time big flows and provides human-friendly interactive graphical representations." @default.
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- W2578400154 date "2016-11-30" @default.
- W2578400154 modified "2023-09-27" @default.
- W2578400154 title "A Traffic Visualization Framework for Monitoring Large-scale Inter- DataCenter Network" @default.
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- W2578400154 doi "https://doi.org/10.5555/3375069.3375108" @default.
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