Name
Abstract | ||
|---|---|---|
ABSTRACTAccurate prediction of network paths between arbitrary hosts on the Internet is of vital importance for network operators, cloud providers, and academic researchers. We present PredictRoute, a system that predicts network paths between hosts on the Internet using historical knowledge of the data and control plane. In addition to feeding on freely available traceroutes and BGP routing tables, PredictRoute optimally explores network paths towards chosen BGP prefixes. PredictRoute's strategy for exploring network paths discovers 4X more autonomous system (AS) hops than other well-known strategies used in practice today. Using a corpus of traceroutes, PredictRoute trains probabilistic models of routing towards prefixes on the Internet to predict network paths and their likelihood. PredictRoute's AS-path predictions differ from the measured path by at most 1 hop, 75% of the time. We expose PredictRoute's path prediction capability via a REST API to facilitate its inclusion in other applications and studies. We additionally demonstrate the utility of PredictRoute in improving real-world applications for circumventing Internet censorship and preserving anonymity online. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3410220.3460107 | Measurement and Modeling of Computer Systems |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rachee Singh | 1 | 23 | 4.54 |
| David Tench | 2 | 45 | 2.33 |
| Phillipa Gill | 3 | 1504 | 114.56 |
| Andrew McGregor | 4 | 271 | 18.36 |