CSIT560 Internet Infrastructure: Switches and Routers Active Queue Management Presented By: Gary Po, Henry Hui and Kenny Chong

Agenda  Why AQM?  In Considerations  AQM Algorithms  Commercial Effort  Conclusions

Why AQM?  Two Classes of Router Algorithms for Congestion Control  What is Congestion?  Congestion avoidance in TCP, is it good enough?  Our Choice : Active Queue Management

What do we consider when implementing AQM?  QoS –Keep Average queue size small –Bounded Delay  Link Utilization –Avoid Global Synchronization –Absorbs bursts without dropping packets  Fairness –Punishes misbehaving flows –Prevent bias against bursty connections  Implementation –Ease of Configurations –Buffer Size Requirement (Large or Small) –Per-flow State Information –Computational Overhead

AQM Algorithms

FIFO + Drop Tail  Problems: –No isolation –No policing –Large queues for high utilizations –Synchronization problem –Lock-out problem

Define Two Threshold Values RED (Random Early Detection)  FIFO scheduling Min thresh Max thresh Average queue length Make Use of Average Queue Length Case 1: Average Queue Length < Min. Thresh Value Admit the New Packet

RED (Cont’d) Min thresh Max thresh Average queue length Case 2: Average Queue Length between Min. and Max. Threshold Value p 1-p Admit the New Packet With Probability p … p 1-p Or Drop the New Packet With Probability 1-p

RED (Cont’d) Min thresh Max thresh Average queue length Case 3: Avg. Queue Length > Max. Threshold Value New Packet will be dropped As no new packets can be admitted, the average queue length decreases. Until the average queue length drops below the max threshold value New packet could be admitted with a probability p … or being dropped with a probability 1-p …

RED Flow Diagram

RED (Cont’d)  Queue Size versus Time Delay is bounded Delay is bounded Global Synchronization solved RED: Queue Size

Unfairness of RED Unresponsive Flow (such as UDP) 32 TCP Flows 1 UDP Flow 32 TCP Flows 1 UDP Flow An unresponsive flow occupies over 95% of bandwidth An unresponsive flow occupies over 95% of bandwidth

CHOKe (CHOose and Keep)  Based on RED  Simple  Designed for fairness  Penalize the unresponsive flow

CHOKe (Cont’d)  Mechanism

CHOKe (Cont’d) Min thresh Max thresh Average queue length Case 1: Average Queue Length < Min. Thresh Value Admit the New Packet

CHOKe (Cont’d) Min thresh Max thresh Average queue length p 1-p Case 2: Avg. Queue Length is between Min. and Max. Threshold Values A packet is randomly chosen from the queue to compare with the new arrival packet If they are from different flows, the same logic in RED applies If they are from the same flow, both packets will be dropped

CHOKe (Cont’d) Min thresh Max thresh Average queue length Case 3: Avg. Queue Length > Max. Threshold Value A random packet will be chosen for comparison If they are from different flows, the new packet will be dropped If they are from the same flow, both packets will be dropped

Evaluate CHOKe’s performance using NS-2

Simulation Scenario 10Mbps 1Mbps 10Mbps UDP TCP UDP TCP sourcedestination router Topology: Dumb-bell Metrics: throughput and queue size

Performance of CHOKe Fair Share Level Bandwidth is evenly shared Bandwidth is evenly shared Unresponsive Flow (UDP) 32 TCP Flows 1 UDP Flow 32 TCP Flows 1 UDP Flow

Parameters  Number of responsive/unresponsive flows  Transfer rate of different flows  Number of random candidates chosen for comparison

CHOKe Simulation  Different Parameters, different performance CHOKe-1 32 TCPs 1 UDP CHOKe-1 32 TCPs 1 UDP CHOKe-2 32 TCPs, 1 UDP of high rate CHOKe-2 32 TCPs, 1 UDP of high rate CHOKe-2 32 TCPs, 3 UDPs of different rate CHOKe-2 32 TCPs, 3 UDPs of different rate CHOKe-2 32 TCPs, 3 UDPs of same rate CHOKe-2 32 TCPs, 3 UDPs of same rate

Evolutions of AQM Algorithms FIFO+DropTail RED FRED CHOKeSAC BLUESFB SRED REM, AVQ, PI Controller  RED –Merits  Early congestion detection  No bias against bursty traffic  No global synchronization –Drawbacks  Difficulty in parameter setting  Insensitivity to traffic load and drain rates  RED –Merits  Early congestion detection  No bias against bursty traffic  No global synchronization –Drawbacks  Difficulty in parameter setting  Insensitivity to traffic load and drain rates  SRED –Merits  Stabilized queue occupancy  Protection from misbehaving flows –Drawbacks  Some per-flow state (zombie list)  RED disadvantages  SRED –Merits  Stabilized queue occupancy  Protection from misbehaving flows –Drawbacks  Some per-flow state (zombie list)  RED disadvantages  FRED –Merits  Good protection from misbehaving flows –Drawbacks  Per-flow state  RED disadvantages  FRED –Merits  Good protection from misbehaving flows –Drawbacks  Per-flow state  RED disadvantages  BLUE –Merits  Simplicity  High throughput –Drawbacks  No early congestion detection (Pdrop updated only on queue overflow or link idle events)  Slow response and dependence on history  BLUE –Merits  Simplicity  High throughput –Drawbacks  No early congestion detection (Pdrop updated only on queue overflow or link idle events)  Slow response and dependence on history  REM –Merits  Low delay and small queues  Independence of the number of users –Drawbacks  Some complexity due to parameters  Low throughput for Web traffic  Inconsistency with TCP sender mechanism; works best with ECN  REM –Merits  Low delay and small queues  Independence of the number of users –Drawbacks  Some complexity due to parameters  Low throughput for Web traffic  Inconsistency with TCP sender mechanism; works best with ECN  LDC –Merits  Sensitivity to traffic load and drain rate  Low delay  Target delay achieved  Intuitive parameters, meaningful to users (target delay) –Drawbacks  Some complexity due to parameters  Low throughput in some cases  LDC –Merits  Sensitivity to traffic load and drain rate  Low delay  Target delay achieved  Intuitive parameters, meaningful to users (target delay) –Drawbacks  Some complexity due to parameters  Low throughput in some cases

Commercial Efforts & Conclusion

Commercial Efforts & Conclusion (Cont’d)  “ Applying AQM over 3G wireless network ” – a paper supported by Motorola Canada Ltd. (Mar. 2003)  3G network, real-time applications have hard time deadlines for packet delivery at the receiver.  Use AQM to avoid long queuing delay and prevent expiring packets.

Commercial Efforts & Conclusion (Cont’d)  AQM improves overall system performance by increasing throughput and reducing end-to-end delay.

Commercial Efforts & Conclusion (Cont’d)  “ Effect of AQM on Web Performance ” – a paper supported by Cisco Systems and IBM. (Aug. 2003)  Proportional Integrator (PI) controller   Random Exponential Marking (REM) controller   Adaptive Random Early Detection (ARED).   IETF proposed standard : Explicit Congestion Notification (ECN)

Commercial Efforts & Conclusion (Cont’d)  ECN has significant impact with AQM scheme in web performance.  Many researches and efforts are going on in the field of AQM.  Simple and Easy to implement