Name
Abstract | ||
|---|---|---|
Data-intensive scientific and commercial applications increasingly require frequent movement of large datasets from one site to the other(s). Despite growing network capacities, these data movements rarely achieve the promised data transfer rates of the underlying physical network due to poorly tuned data transfer protocols. Accurately and efficiently tuning the data transfer protocol parameters i... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TPDS.2018.2790948 | IEEE Transactions on Parallel and Distributed Systems |
Keywords | Field | DocType |
Throughput,Tuning,Concurrent computing,Data transfer,Real-time systems,Heuristic algorithms,Pipeline processing | Data transmission,Computer science,Real-time computing,Feedback loop,HARP,Sampling (statistics),Concurrent computing,Estimation theory,Throughput,Network model | Journal |
Volume | Issue | ISSN |
29 | 6 | 1045-9219 |
Citations | PageRank | References |
6 | 0.47 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Engin Arslan | 1 | 116 | 12.12 |
| Kosar, Tevfik | 2 | 614 | 48.67 |