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| Authors: | Eduard Glatz, Stelios Mavromatidis, Bernhard Ager, Xenofontas Dimitropoulos |
| Group: | Communication Systems |
| Type: | Inproceedings |
| Title: | Visualizing big network traffic data using frequent pattern mining and hypergraphs |
| Year: | 2012 |
| Month: | November |
| Pub-Key: | Gla12b |
| Book Titel: | First IMC Workshop on Internet Visualization (WIV 2012) |
| Keywords: | traffic analysis, visualization |
| Publisher: | Springer |
| Abstract: | Visualizing communication logs, like NetFlow records, is extremely useful for numerous tasks that need to analyze network trac traces, like network planning, performance monitoring, and troubleshooting. Communication logs, however, can be massive, which necessitates designing eective visualization techniques for large data sets. To address this problem, we introduce a novel network trac visualization scheme based on the key ideas of 1) exploiting frequent itemset mining (FIM) to visualize a succinct set of interesting trac patterns extracted from large traces of communication logs; and 2) visual- izing extracted patterns as hypergraphs that clearly display multi-attribute associations. We demonstrate case studies that support the utility of our vi- sualization scheme and show that it enables the visualization of substantially larger data sets than existing network trac visualization schemes based on parallel-coordinate plots or graphs. For example, we show that our scheme can easily visualize the patterns of more than 41 million NetFlow records. |
| Location: | Boston, Massachusetts, USA |
| Resources: | [BibTeX] |
