arrow
Return

Congestion Control Scheme Performance Analysis Based on Nonlinear RED

delete2017-12-01
delete47
PRE
AI
C
Chenwei Feng
L
Lianfen Huang *
X
Xu Cheng
Y
Yao‐Chung Chang
DOI:10.1109/JSYST.2014.2375314delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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.
Keywords:
Active queue management (AQM)
congestion control
nonlinear
random early detection (RED)
traffic load
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
IEEE Open Journal of Circuits and Systems
IF:
2.4
Papers:
4.5K
Citations:
387

Organization

X
xiamen university
Scholars:
5.8W
Papers: 3.8W
Citations: 67