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Joo, Changhee
Learning, Modeling, and Networking
Research Interests
  • Learning, modeling, networking, resource allocation, stochastic optimization, distributed computing, low complexity

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A hybrid active queue management for stability and fast adaptation

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Title
A hybrid active queue management for stability and fast adaptation
Author
Joo, ChangheeBahk, SaewoongLumetta, Steven S.
Keywords
active queue management (AQM); random early detection (RED); response time; stability
Issue Date
2006-03
Publisher
KOREAN INST COMMUNICATIONS SCIENCES (K I C S)
Citation
JOURNAL OF COMMUNICATIONS AND NETWORKS, v.8, no.1, pp.93 - 105
Abstract
The domination of the Internet by TCP-based services has spawned many efforts to provide high network utilization with low loss and delay in a simple and scalable manner. Active queue management (AQM) algorithms attempt to achieve these goals by regulating queues at bottleneck links to provide useful feedback to TCP sources. While many AQM algorithms have been proposed, most suffer from instability, require careful configuration of non-intuitive control parameters, or are not practical because of slow response to dynamic traffic changes. In this paper, we propose a new AQM algorithm, hybrid random early detection (HRED), that combines the more effective elements of recent algorithms with a random early detection (RED) core. HRED maps instantaneous queue length to a drop probability, automatically adjusting the slope and intercept of the mapping function to account for changes in traffic load and to keep queue length within the desired operating range. We demonstrate that straightforward selection of HRED parameters results in stable operation under steady load and rapid adaptation to changes in load. Simulation and implementation tests confirm this stability, and indicate that overall performances of HRED are substantially better than those of earlier AQM algorithms. Finally, HRED control parameters provide several intuitive approaches to trading between required memory, queue stability, and response time.
URI
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DOI
10.1109/JCN.2006.6182909
ISSN
1229-2370
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EE_Journal Papers
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