Name
Abstract | ||
|---|---|---|
With the development of cloud computing in recent years, data center networks have become a hot topic in both industrial and academic communities. Previous studies have shown that elephant flows, which usually carry large amount of data, are critical to the efficiency of data centers. In this paper, we study the flow scheduling problem in data centers with a focus on elephant flows. By applying stable matching theory, the scheduling problem is modeled and some useful method is complemented. Then, we propose Fincher, an efficient scheme leveraging Software-Defined Networking (SDN) to reduce latency and avoid congestions in data centers. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/PCCC.2015.7410343 | IPCCC |
Keywords | Field | DocType |
Fincher,elephant flow scheduling problem,stable matching theory,data center networks,cloud computing,software-defined networking,SDN | Job shop scheduling,Fair-share scheduling,Computer science,Scheduling (computing),Latency (engineering),Flow shop scheduling,Computer network,Real-time computing,Data center,Elephant flow,Cloud computing,Distributed computing | Conference |
ISSN | Citations | PageRank |
1097-2641 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxiang Zhang | 1 | 11 | 15.58 |
| Lin Cui | 2 | 66 | 8.35 |
| Qiao Chu | 3 | 0 | 0.34 |