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EECS 122: Introduction to Computer Networks Transport Layer - Advanced Variations 

EECS 122: Introduction to Computer Networks Transport Layer - Advanced Variations . Computer Science Division Department of Electrical Engineering and Computer Sciences University of California, Berkeley Berkeley, CA 94720-1776. Quick Review. Slow-Start: cwnd++ upon every new ACK

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EECS 122: Introduction to Computer Networks Transport Layer - Advanced Variations 

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  1. EECS 122: Introduction to Computer Networks Transport Layer - Advanced Variations  Computer Science Division Department of Electrical Engineering and Computer Sciences University of California, Berkeley Berkeley, CA 94720-1776

  2. Quick Review • Slow-Start: cwnd++ upon every new ACK • Congestion avoidance: AIMD if cwnd > ssthresh • ACK: cwnd = cwnd + 1/cwnd • Drop: ssthresh =cwnd/2 and cwnd=1 • Fast Recovery: • duplicate ACKS: cwnd=cwnd/2 • Timeout: cwnd=1

  3. TCP Flavors • TCP-Tahoe • cwnd =1 whenever drop is detected • TCP-Reno • cwnd =1 on timeout • cwnd = cwnd/2 on dupack • TCP-newReno • TCP-Reno + improved fast recovery • TCP-Vegas, TCP-SACK

  4. TCP Vegas • Improved timeout mechanism • Decrease cwnd only for losses sent at current rate • avoids reducing rate twice • Congestion avoidance phase: • compare Actual rate (A) to Expected rate (E) • if E-A > , decrease cwnd linearly • if E-A < , increase cwnd linearly • rate measurements ~ delay measurements • see textbook for details!

  5. TCP-SACK • SACK = Selective Acknowledgements • ACK packets identify exactly which packets have arrived • Makes recovery from multiple losses much easier

  6. Standards? • How can all these algorithms coexist? • Don’t we need a single, uniform standard? • What happens if I’m using Reno and you are using Tahoe, and we try to communicate?

  7. Equation-Based CC • Simple scenario • assume a drop every k’th RTT (for some large k) • w, w+1, w+2, ...w+k-1 DROP (w+k-1)/2, (w+k-1)/2+1,... • Observations: • In steady state: w= (w+k-1)/2 so w=k-1 • Average window: 1.5(k-1) • Total packets between drops: 1.5k(k-1) • Drop probability: p = 1/[1.5k(k-1)] • Throughput: T ~ (1/RTT)*sqrt(3/2p)

  8. Equation-Based CC • Idea: • Forget complicated increase/decrease algorithms • Use this equation T(p) directly! • Approach: • measure drop rate (don’t need ACKs for this) • send drop rate p to source • source sends at rate T(p) • Good for streaming audio/video that can’t tolerate the high variability of TCP’s sending rate

  9. Question! • Why use the TCP equation? • Why not use any equation for T(p)?

  10. Cheating • Three main ways to cheat: • increasing cwnd faster than 1 per RTT • using large initial cwnd • Opening many connections

  11. x A B y D E Increasing cwnd Faster y C x increases by 2 per RTT y increases by 1 per RTT Limit rates: x = 2y x

  12. x A B y D E Increasing cwnd Faster

  13. x A B y D E Larger Initial cwnd x starts SS with cwnd = 4 y starts SS with cwnd = 1

  14. x A B y D E Open Many Connections • Assume • A starts 10 connections to B • D starts 1 connection to E • Each connection gets about the same throughput • Then A gets 10 times more throughput than D

  15. x A B y D E Cheating and Game Theory D  Increases by 1 Increases by 5 A Increases by 1 Increases by 5 (x, y) • Too aggressive • Losses • Throughput falls Individual incentives: cheating pays Social incentives: better off without cheating Classic PD: resolution depends on accountability

  16. Lossy Links • TCP assumes that all losses are due to congestion • What happens when the link is lossy? • Recall that Tput ~ 1/sqrt(p) where p is loss prob. • This applies even for non-congestion losses

  17. Example p = 0 p = 1% p = 10%

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