Adaptive Control for TCP Flow Control Thesis Presentation Amir Maor

13/6/02 Presentation Structure 8Introduction 8AdaVegas intuition 8AdaVegas simulation results 8Adaptive mechanism for TCP new Reno 8Conclusion

13/6/02 Flow Control TCP communicates over various interconnected data networks. Network exact characteristics are unknown and vary with time. TCP has to continuously update its sending rate efficiently and fairly.

13/6/02 Flow Control Existing Solutions TCP NewReno The sending rate increases continuously until a packet is dropped. Two Phases –Slow Start – increase exponentially –Congestion Avoidance – increase linearly

13/6/02 NewReno Dynamics

13/6/02 Flow Control Existing Solutions TCP Vegas Stop increasing rate before swamping the network Delay  (propagation delay) + (queuing)  Estimates number of queued packets Decrease Rate Linearly  >  Exit  >  - <<<< Double Rate  <  Increase Rate Linearly  <  Slow StartCongestion Avoidance

13/6/02 Vegas Dynamics

13/6/02 Reno And Vegas Dynamics

13/6/02 Related Work – Chiu & Jain AIMD converges to stable and fair operating point

13/6/02 Related Work – Bansal & Barakrishnan k+l>0; k>=0 or l>=0

13/6/02 Related Work – Bansal & Barakrishnan

13/6/02 Related Work – Bansal & Barakrishnan

13/6/02 Progress 4Introduction 8AdaVegas intuition 8AdaVegas simulation results 8Adaptive mechanism for TCP new Reno 8Conclusion

13/6/02 How Adaptive Is Vegas? Vegas changes the sending rate Vegas does not change the way it changes the sending rate +1 seg/RTT ; -1 seg/RTT ; -0.5*(rate) Is this way optimal?

13/6/02 Linear Increase Constant Optimal Value or Painful Compromise ?

13/6/02 Linear Increase Constant Optimal Value or Painful Compromise ?

13/6/02 Making Vegas Adaptive The larger the available bandwidth the larger the increase constant How do we know how large the available bandwidth is? –We don’t ! BUT we can take a pretty good guess by using recent history

13/6/02 Making Vegas Adaptive Alpha & Beta parameters

13/6/02 AdaVegas Dynamics

13/6/02 Progress 4Introduction 4AdaVegas intuition 8AdaVegas simulation results 8Adaptive mechanism for TCP new Reno 8Conclusion

13/6/02 Simulation Model ON/OFF users using heavy tailed distribution Evaluation criteria: –Line utilization, queue size,loss rate,fairness # users ON mean time Evaluation criteria SOURCE 1 SOURCE 2 SOURCE 3 SOURCE N SINK 1 SINK 2 SINK 3 SINK N ROUTER 1 ROUTER msec 20Mb /sec 1 msec 100Mb/sec 1 msec 100Mb/sec SOURCE 1 SOURCE 2 SOURCE 3 SOURCE N SINK 1 SINK 2 SINK 3 SINK N ROUTER 1 ROUTER msec 20Mb /sec 1 msec 100Mb/sec 1 msec 100Mb/sec

13/6/02 Results - Utilization ON mean time # users Evaluation criteria

13/6/02 Results – Queue Size ON mean time # users Evaluation criteria

13/6/02 Results – Fairness Index ON mean time # users Evaluation criteria

13/6/02 Results – Loss Rate ON mean time # users Evaluation criteria

13/6/02 Heterogeneous Environments Different RTT

13/6/02 Heterogeneous Environments AdaVegas and Vegas

13/6/02 Progress 4Introduction 4AdaVegas intuition 4AdaVegas simulation results 8Adaptive mechanism for TCP new Reno 8Conclusion

13/6/02 Import AdaVegas to NewReno? Relation between increase constant and available bandwidth does not hold in NewReno

13/6/02 NewReno and High Increase Rate

13/6/02 Congestion Avoidance - Barking up the wrong tree?

13/6/02 Progress 4Introduction 4AdaVegas intuition 4AdaVegas simulation results 4Adaptive mechanism for TCP new Reno 8Conclusion

13/6/02 Conclusion & Future Work AdaVegas is able to adapt better to changing environments Research on adaptive mechanisms for NewReno should focus on “Slow Start” as well Develop adaptive mechanism for NewReno Make AdaVegas’ increase parameter unbound

13/6/02 Symmetric TCP Vegas