Name
Abstract | ||
|---|---|---|
The inference of the network traffic matrix from partial measurement data becomes increasingly critical for various network engineering tasks, such as capacity planning, load balancing, path setup, network provisioning, anomaly detection, and failure recovery. The recent study shows it is promising to more accurately interpolate the missing data with a 3-D tensor as compared with the interpolation... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNET.2018.2819504 | IEEE/ACM Transactions on Networking |
Keywords | Field | DocType |
Tensile stress,Matrix decomposition,Monitoring,Correlation,Internet,Data models,Interpolation | Data modeling,Matrix completion,Tensor,Load balancing (computing),Matrix (mathematics),Computer science,Matrix decomposition,Algorithm,Mean squared error,Missing data,Distributed computing | Journal |
Volume | Issue | ISSN |
26 | 3 | 1063-6692 |
Citations | PageRank | References |
2 | 0.36 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kun Xie | 1 | 197 | 38.39 |
| Can Peng | 2 | 2 | 0.70 |
| Xin Wang | 3 | 408 | 51.21 |
| Gaogang Xie | 4 | 632 | 74.19 |
| Jigang Wen | 5 | 130 | 14.67 |
| Jiannong Cao | 6 | 5226 | 425.12 |
| Dafang Zhang | 7 | 272 | 44.21 |
| Zheng Qin | 8 | 471 | 57.29 |