Paper Info
Title
A Comprehensive Performance Analysis of Random Early Detection Mechanism
Abstract
One of the most promising active queue management schemes being proposed for deployment in the Internet is the Random Early Detection (RED) scheme. However, research results on RED performance are highly mixed, especially in the field of tuning its parameters. In this paper, a comprehensive performance analysis of RED is presented. We revisit some features in RED and study them in greater detail. We point out that RED, in general, does not possess proportional loss between flows as claimed and widely adopted in previous research. We suggest the generalization of the PASTA property and give a proof for TCP flows. We also evaluate the performance of the Exponential Weighted Moving Average (EWMA) algorithm in RED. We find that EWMA in RED is an unbiased estimator of the average queue-length, regardless of the weighting value wq. We also point out the theoretical and practical limits of EWMA in RED. Finally, we propose the use of fuzzy EWMA to RED (fuzzy RED) to alleviate the inflexibility of RED tuning. We use simulations to evaluate the performance of fuzzy RED and compare it with other versions of RED. Our simulations show that, in the case of a high workload and a high level of variation, fuzzy RED, by tracking system variation in an on-line manner, improves RED performance in a number of important router-based metrics like packet loss rate, average queueing delay, link utilization, and global power.
Year
DOI
Venue
2004
10.1023/B:TELS.0000011194.77405.30
Telecommunications Systems
Keywords
Field
DocType
Packet Loss,Packet Loss Rate,Exponential Weight Move Average,Exponential Weight,Link Utilization
Random early detection,Weighting,Active queue management,Computer science,Fuzzy logic,Algorithm,EWMA chart,Packet loss,Real-time computing,Bias of an estimator,Queueing theory,Statistics
Journal
Volume
Issue
ISSN
25
1-2
1572-9451
Citations 
PageRank 
References 
6
0.54
16
Authors
2
Name
Order
Citations
PageRank
Tuan Anh Trinh19710.82
Sándor Molnár230638.56