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Active Queue Management in Internet and Wireless Networks X. Deng, S. Yi, G. Kesidis and C. R. Das The Pennsylvania State University Stabilized queue size.

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Presentation on theme: "Active Queue Management in Internet and Wireless Networks X. Deng, S. Yi, G. Kesidis and C. R. Das The Pennsylvania State University Stabilized queue size."— Presentation transcript:

1 Active Queue Management in Internet and Wireless Networks X. Deng, S. Yi, G. Kesidis and C. R. Das The Pennsylvania State University Stabilized queue size with varying traffic loads and link delays Reduced packet loss and response time A Unified Framework for Design and Analysis of AQM Interpreting and Calibrating AQM parameters as PID controlling components to the TCP plant module. New Controlling Components in AQM Derivative Control (D control): Use change of packet arrival rate over time as the congestion indicator, in addition to the instantaneous packet arrival rate (P control) and router queue length (I control). Adaptive Control: The controlling parameters adaptively changes with the steady state packet marking probability p0 using update functions m and l, which increase monotonically (APID). Virtual Queue Control: A New Combination of rate-based and queue-based control (QRVQ) Modeling TCP/AQM A control-theoretic model for TCP and RED [Hollot’01]. Extend this model to incorporate more end-system and AQM controller Proportional-Integral-Derivative (PID) controller – A unified framework for design and analysis of AQM schemes. System stability is related to network and traffic condition – use Adaptive Control for a better stabilized and robust system AQM for Wireless Networks More variable in bandwidth and delay Uplink/Downlink asymmetry ABSTRACT MOTIVATION METHOD RESULTS CONCLUSIONS Queue AQM TCP-Reno FIFO In this research, we use a control theoretic approach to develop a generic framework for analyzing various active queue management (AQM) schemes as proportionally-integral-derivative (PID) controllers. Based on this PID model, we propose an adaptive control mechanism to improve the system stability and performance under changing network conditions. A simulation study under a wide range of traffic conditions suggests that the proposed algorithms outperform the existing AQM schemes in achieving better system performance and stability. We then apply the AQM concept to achieve fairness bandwidth allocation between downlink and uplink traffic in wireless LANs Queue TCP dynamic queue dynamic AQM p W q time delay R secs Better Fairness between uplink/downlink traffic by using PI control over packet arrival rate (AVQ) for uplink traffic in Wireless LAN N: Number of connections W: TCP congestion window R: Round trip time : Packet arrival rate q: router queue size p: packet drop/mark probability Putting everything together : GtGq - METHOD (CONT) Use Rate-based AQM for Uplink Traffic in Wireless LANs Ensure fairness for downlink/uplink traffic Can work together with downlink queue-based AQM for Queue management and QoS provisioning Linearized TCP/AQM System AQM(Gc)TCP (Gt)Queue (Gq) Plant (Gp) Controller rate based AQM(Gc)TCP (Gt)Queue (Gq) AQM(Gc) TCP (Gt) Downlink Uplink Various AQM Schemes can be classified as different types of PID Controllers. Addition of derivative and adaptive control improves the stability of the system under varying plant configurations. A rate based AQM for uplink traffic in Wireless LANs enhances the fairness and improves the QoS for downlink traffic. No AQM With AVQ SYSTEM MODEL


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