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Analysis of Active Queue Management

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Analysis of Active Queue Management Jae Chung and Mark Claypool Computer Science Department Worcester Polytechnic Institute Worcester, Massachusetts, USA – PowerPoint PPT presentation

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Title: Analysis of Active Queue Management


1
Analysis of Active Queue Management
Jae Chung and Mark Claypool
Computer Science Department Worcester Polytechnic
Institute Worcester, Massachusetts, USA
http//perform.wpi.edu/
2
Active Queue Management
  • Advantages
  • Reduce packet losses
  • (due to queue overflow)
  • Reduce queuing delay

3
Related Work Analysis of AQM
  • Control Theory Approach (Hollot, Infocom 01)
  • Model TCP and AQM Behaviors (Laplace domain).
  • Apply Classical Control Theory (through
    analysis).
  • Params not obvious for understanding control
    info.
  • Queue Law (Firoiu, Infocom 00)
  • Model Average TCP Throughput and the behavior of
    Average Queue Length at congested router.
  • Shows the impact of traffic parameters on AQM.
  • Not suitable for system stability analysis.
  • Good for analyzing and configuring AQMs using
    average queue.

4
Contribution
  • Extend Firoius to a General Queue Law
  • Simplify the queue law to better illustrate the
    effect of traffic parameters on AQM.
  • Extend the queue law to support Explicit
    Congestion Notification (ECN) and study the
    impact of ECN on AQM congestion control.
  • Analysis of RED-Family AQM
  • Evaluate RED-Family AQMs (RED, Gentle RED and
    Adaptive RED)
  • Demonstrate ECN gains on packet loss rates.

5
Outline
  • Introduction
  • Queue Law
  • Impact of ECN
  • RED Family AQM
  • Analysis of REDs
  • Summary

6
Average TCP Window(Bulk Transfers)
  • Function of congestion notification probability
    (CNP) only.
  • Not affected by the number of flows (N), RTT or
    Service Rate (SR).
  • Same for ECN and non-ECN flows.

7
The GeneralQueue Law
8
General Queue Law Validation
  • Used average TCP throughput model from (Padhye,
    Sigcomm 1998).
  • Works well for ECN.
  • Inaccurate for non-ECN The TCP throughput model
    does not effectively model Retransmission Timeout.

9
Effect of Limiting TCP Window
  • Window-limited (and short-lived) flows consume
    less bandwidth.
  • Yet, they are less responsive to congestion
    notification

10
Outline
  • Introduction
  • Queue Law
  • Impact of ECN
  • RED Family AQM
  • Analysis of REDs
  • Summary

11
Impact of ECN on AQM
  • ECN has no signaling packet loss.
  • Requires higher CNP to keep the average queue at
    the same level.
  • Helps the control system stability as less
    sensitive to CNP changes.

12
Outline
  • Introduction
  • Queue Law
  • Impact of ECN
  • RED Family AQM
  • Analysis of REDs
  • Summary

13
RED-Family AQM
14
Simulation Configuration
  • Dumbbell topology (SR 20Mbps, Q 500 pkts)
  • Increase of TCP flows (N 50300) each 50 sec.
  • Implicit (drop) and ECN (configurations shown)

Q 500 pkts
SR 20 Mbps
RTLD 80 ms
15
CongestedRouter Queue(ECN Results)
16
Packet Loss Rate
17
Contribution
  • The General Queue Law
  • Illustrated the effect of traffic parameters on
    AQM.
  • Discussed the impact of ECN traffic on AQM.
  • Provides mean to configure RED for ECN traffic.
  • RED-Family AQM Evaluation
  • Showed the ECN gain on packet loss rate and the
    limitation of AQMs without ECN over Drop-Tail.
  • Provided an analysis on RED-Family AQM
  • Gentle RED may result in an unstable queue
    oscillation.
  • Adaptive RED can support a wide range of traffic
    loads.

18
Future Work
  • Extend our study to a mixture of ECN and
    non-ECN TCP flows.
  • Building an adaptive AQM technique that makes
    use of our queue law to quickly adapt to a
    well-configured state in the presence of
    changing network loads.

19
Analysis of Active Queue Management
Jae Chung and Mark Claypool
Computer Science Department Worcester Polytechnic
Institute Worcester, Massachusetts, USA
http//perform.wpi.edu/
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