Name
Abstract | ||
|---|---|---|
Congestion control has become a research focus with the development of network communication technology. Random early detection (RED) for queue management techniques is the most effective method. However, RED is particularly sensitive to the traffic load and the parameters of the scheme itself. When the traffic load is low, the bandwidth is underutilized, whereas when the traffic load is high, the delay is large. This paper presents a minimal adjustment to RED called three-section random early detection (TRED) based on nonlinear RED, in which the packet dropping probability function is divided into three sections to distinguish between light, moderate, and high loads to achieve a tradeoff in the delay and the throughput between low and high traffic loads. The NS2 simulation results show that TRED effectively improves the insufficiencies of RED to achieve better congestion control. Additionally, very little work needs to be done to migrate from RED to TRED on Internet routers because only the packet dropping probability profile is adjusted. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSYST.2014.2375314 | IEEE Systems Journal |
Keywords | Field | DocType |
Active queue management (AQM),congestion control,nonlinear,random early detection (RED),traffic load | Random early detection,Weighted random early detection,Computer science,Active queue management,Network packet,Computer network,Real-time computing,Network congestion,Throughput,Queue management system,Network traffic control | Journal |
Volume | Issue | ISSN |
PP | 99 | 1932-8184 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wu-chun Feng | 1 | 2812 | 232.50 |
| Lianfen Huang | 2 | 132 | 32.83 |
| Chengxin Xu | 3 | 0 | 1.69 |
| Chang, Y.-C. | 4 | 4 | 4.10 |