Name
Title | ||
|---|---|---|
A learning-based measurement framework for traffic matrix inference in software defined networks. |
Abstract | ||
|---|---|---|
•A framework for estimating flow sizes in software defined networks is proposed.•An optimization formulation for providing optimal flow aggregates is proposed.•An algorithm for measuring the most informative flows is presented. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compeleceng.2017.11.020 | Computers & Electrical Engineering |
Keywords | Field | DocType |
Network measurement and inference,Traffic matrix estimation,Software defined networking,Compressed sensing,Multi-armed bandit algorithms | Flow network,Content-addressable memory,Ternary content addressable memory,Inference,Computer science,Matrix (mathematics),Real-time computing,Software-defined networking,Distributed computing | Journal |
Volume | Issue | ISSN |
66 | C | 0045-7906 |
Citations | PageRank | References |
1 | 0.36 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mehdi Malboubi | 1 | 29 | 5.90 |
| Shu-Ming Peng | 2 | 1 | 0.36 |
| Puneet Sharma | 3 | 2341 | 188.96 |
| Chen-Nee Chuah | 4 | 2006 | 161.34 |