Paper
1 July 2002 Multivariate analysis for performance evaluation of active-queue-management mechanisms in the Internet
Author Affiliations +
Proceedings Volume 4865, Internet Performance and Control of Network Systems III; (2002) https://doi.org/10.1117/12.473385
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States
Abstract
AQM (Active Queue Management) mechanism, which performs congestion control at a router for assisting the end-to-end congestion control mechanism of TCP, has been actively studied by many researchers. For instance, RED (Random Early Detection) is a representative AQM mechanism, which drops arriving packets with a probability being proportional to its average queue length. The RED router has four control parameters, and its effectiveness heavily depends on a choice of these control parameters. This is why many researches on the parameter tuning of RED control parameters have been performed. However, most of those studies have investigated the effect of RED control parameters on its performance from a small number of simulation results. In this paper, we therefore statistically analyze a great number of simulation results using the multivariate analysis. We quantitatively show the relation between RED control parameters and its performance.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tomoya Eguchi, Hiroyuki Ohsaki, and Masayuki Murata "Multivariate analysis for performance evaluation of active-queue-management mechanisms in the Internet", Proc. SPIE 4865, Internet Performance and Control of Network Systems III, (1 July 2002); https://doi.org/10.1117/12.473385
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Statistical analysis

Computer simulations

Control systems

Internet

Analytical research

Detection and tracking algorithms

Linear filtering

Back to Top