Name
Abstract | ||
|---|---|---|
BGP measurement is important for monitoring and understanding the Internet anomalies. Most of the previous works on BGP measurement rely on aggregated statistics from BGP monitors, e.g., total updates. However, BGP events may have quite limited visibility. Therefore, merely investigating aggregated data may lead to misunderstanding Internet instability, e.g., overestimating the impact of monitor-local events. In this empirical study, we demonstrate how BGP data are distributed among a large number of monitors. We define eleven features as the analysis targets, and three metrics to quantify disparity. We apply the method to 1.14 TB data and find that the distribution of most of the features is quite uneven, and different types of feature illustrate different levels of disparity. We also observe long periods of persistent high disparity, and a small set of cross-feature highly active monitors. Our analysis highlights the necessity of per-monitor data analysis in future BGP measurement study. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/LCN.2016.13 | 2016 IEEE 41st Conference on Local Computer Networks (LCN) |
Keywords | Field | DocType |
measurement study,BGP instabilities distribution disparity,BGP measurement,Internet anomaly monitoring,Internet instability,Border Gateway Protocol,interdomain routing protocol | Data mining,Visibility,Computer science,Computer network,Distributed database,Small set,Empirical research,The Internet | Conference |
ISSN | ISBN | Citations |
0742-1303 | 978-1-5090-2055-3 | 0 |
PageRank | References | Authors |
0.34 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meng Chen | 1 | 5 | 3.13 |
| Mingwei Xu | 2 | 644 | 97.00 |
| Yuan Yang | 3 | 83 | 19.06 |
| Li Qing | 4 | 5 | 1.89 |