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Diffusion Mechanisms for Active Queue Management Department of Electrical and Computer Engineering University of Delaware May 19th / 2004 Rafael Nunez.

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Presentation on theme: "Diffusion Mechanisms for Active Queue Management Department of Electrical and Computer Engineering University of Delaware May 19th / 2004 Rafael Nunez."— Presentation transcript:

1 Diffusion Mechanisms for Active Queue Management Department of Electrical and Computer Engineering University of Delaware May 19th / 2004 Rafael Nunez nunez@ece.udel.edu Gonzalo Arce arce@ece.udel.edu

2 2 Diffusion Mechanisms for Active Queue Management Image Processing Approaches to AQM: There is an intimate link between printing technologies and Active Queue Management.

3 3 The Internet Today TCP: de facto congestion control protocol. 90% of Internet traffic.

4 4 Congestion Desirable control: distributed, simple, stable and fair.

5 5 Simplest Congestion Control: Tail Dropping Problems with tail dropping: Penalizes bursty traffic Discriminates against large propagation delay connections. Global synchronization.

6 6 Active Queue Management (AQM) Router becomes active in congestion control. Random Early Detection (Floyd and Jacobson, 1993). RED has been deployed in some Cisco routers.

7 7 Random Early Detection (RED) Random packet drops in queue. Drop probability based on average queue: Four parameters:  q min  q max  P max  w q (overparameterized)

8 8 Queue Behavior in RED

9 9 Queue Behavior in RED (2) 20 new flows every 20 seconds Wq = 0.01 Wq = 0.001

10 10 How to overcome these problems… Adaptive RED, REM, GREEN, BLUE,… Problems:  Over-parameterization  Not easy to implement in routers  Not much better performance than drop tail

11 11 REM vs. RED

12 12 Diffusion Mechanisms: Exploiting Image Processing Our solution Based on digital halftoning Halftoning is a successful printing technique: from newspapers to laser printers

13 13 Digital Halftoning Original Image Ordered Dither Error Diffusion

14 14

15 15 Probability of Marking a Packet Gentle RED function closely follows: (A)

16 16 Evolution of the Congestion Window TCP in steady state: (B)

17 17 Traffic in the Network Congestion Window = Packets In The Pipe + Packets In The Queue Or: (C) From (A), (B), (C), and knowing that : where

18 18 Probability Function

19 19 Error Diffusion Packet marking is analogous to halftoning:  Convert a continuous gray-scale image into black or white dots  Packet marking reduces to quantization Error diffusion: The error between input (continuous) and output (discrete) is incorporated in subsequent outputs.

20 20 Diffusion Mechanism ≥

21 21 Diffusion Mechanism ≥

22 22 Diffusion Mechanism ≥

23 23 Diffusion Mechanism ≥

24 24 Diffusion Mechanism ≥

25 25 Diffusion Mechanism ≥

26 26 Diffusion Mechanism ≥

27 27 Diffusion Mechanism ≥

28 28 Diffusion Mechanism ≥

29 29 Diffusion Mechanism ≥

30 30 Diffusion Mechanism ≥

31 31 Diffusion Mechanism ≥

32 32 Algorithm Summary Diffusion Early Marking decides whether to mark a packet or not as: Where: M=2, b 1 =2/3, b 2 =1/3 Remember:

33 33 Diffusion Mechanisms for Active Queue Management RESULTS

34 34 Window Size RED Diffusion Based Larger congestion window  more data!

35 35 Stability of the Queue 100 long lived connections (TCP/Reno, FTP) Desired queue size = 30 packets RED Diffusion Based

36 36 Changing the number of flows 20 new flows every 20 seconds RED Diffusion Based

37 37 Conclusions Digital halftoning is a mature technique that can be used in AQM. Advantages:  Increased stability  Simpler (only one parameter)  Increased throughput Current Work:  Parameter optimization  Complete benchmarking  Additional traffic control applications

38 Thank you! Department of Electrical and Computer Engineering University of Delaware May 19th / 2004 Rafael Nunez nunez@ece.udel.edu Gonzalo Arce arce@ece.udel.edu


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