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TCP-Carson A Loss-event Based Adaptive AIMD Protocol for Long-lived Flows Hariharan Kannan Advisor: Prof. M Claypool Co-Advisor: Prof. R Kinicki Reader: Prof. D Finkel
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Outline Introduction TCP Behavior TCP-Carson Evaluation Summary Future Work
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Introduction Modern Internet Short-lived flows e.g. HTTP Streaming media e.g. Real audio Real-time applications e.g. VoIP services Long-lived flows e.g. FTP Heavy tailed 80% bytes are from few connections [Matta, ‘01] Use TCP 80% of traffic is TCP [Hidenari, ‘97] Responsive to congestion – Internet stability No loss Router Support to TCP like behavior More applications are built on top of TCP Optimize long-lived flow performance in TCP like fashion Long-lived
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Modifications to TCP TCP – Two phases –Slow Start: (till first loss of packet) Aim: Rough estimate of available bandwidth. Congestion Manager [Bala, ’99], TCP Fast Start [Venkat, ‘98] –Congestion Avoidance: Aim: Optimize window-size, react to network congestion Reno, New-Reno, Vegas, Tahoe AIMD [Yang, ‘00]: window size = f (increase “a”, decrease “1-b”) –Conventional TCP (1, 0.5) –Other Equations: a=3b/(2-b), a=4(1-b²)/3 –TCP-Carson * –TCP variant, built on top of RENO –Window-based –Fully reliable –Responsive to Congestion * Carson City: Located in the State of Nevada, Population: 52457, Founded 1858 For more details visit http://www.carson-city.nv.us/http://www.carson-city.nv.us/
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The Probing Problem drop s
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TCP-Carson Detects Steady State –Losses are periodic –Loss interval: Interval in packets between two successive losses Adapt responsiveness (reaction) –Adapt “a”, “b”: (increase, decrease) Benefits: Increase throughput, reduce loss, reduce window-size variance
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Outline Introduction TCP Behavior –Congestion Window –Loss interval TCP-Carson Evaluation Summary
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Topology R2 R1 r1 r2 r3 s3 s2 s1 1 Mb, 40ms 2 Mb, 10ms Drop tail Q = 15 Drop tail Q = 15
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TCP – Cwnd Behavior 1161 Steady UnsteadySteady RTX-TO - b/w + b/w
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TCP – Loss interval Loss Interval : Number of packets between successive loss events 1161 Steady Unsteady
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Outline Introduction TCP Behavior TCP-Carson –Steady State Detection Metrics Mechanism –Algorithm Evaluation Summary
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Steady State Detection - Metrics 11 16
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Steady State Detection - Metrics 1 116
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Steady State Detection - Algorithm Metric : Weighted Average Loss Interval –Used in TFRC [Floyd, ‘01] –Evaluated overlapping and distinct windows –Evaluated window sizes from 4 – 32 –Chose sliding-32 –Equal weights to recent 16 –Exponentially decreasing weights for prior 16 wt i = 1, 1 ≤ i ≤ 16 = 1 - [(i – n/2)/(n/2 +1)], 17 ≤ i ≤ 32 123………313233
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Steady State Detection - Algorithm When Steady? –wali(i+1) = wali(i) ± [ 0.1 * wali(i)] When Unsteady? –wali(i+1) != wali(i) ± [ 0.1 * wali(i)] –Retransmission timeout –No loss for long time See how it works!!!
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Steady State – 10 Flows
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481684 Steady State – Varying # of flows 481684
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TCP–Carson : Algorithm AIMD Table: detect_state(loss_interval) if (steady) { go_up() } if (unsteady) {go_down()}//become TCP Okay dude!!! Show me the results!!!! “a”“b” 0.1480.875 0.2500.750 0.600 1.0000.500 TCP (start here)
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Evaluation 1 TCP-Carson 1 TCP-Carson, 1 CBR 1 TCP-Carson, 1 TCP-Reno 4 TCP-Carson, 4 TCP-Reno 7 TCP-Carson, 1 TCP-Reno 1 TCP-Carson, 7 TCP-Reno 8 TCP-Carson 20 TCP-Carson Varying flow life-times – Varying number of flows
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1TCP-Carson
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1 TCP-Carson, 1 CBR(0.5Mb) 1 Carson, 1 UDP 1 Carson
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1TCP-Carson, 1TCP-Reno
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4-Carson, 4-Reno
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8 TCP-Carson flows
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Evaluation CarsonReno Avg Cwnd 27.7 24.4 Loss 121 167 Thruput 0.948 0.944 Single Flow CarsonReno Avg Cwnd 14.6 12.6 Loss 124 180 Thruput 0.511 0.437 1-Carson, 1-Reno CarsonReno Avg Cwnd 8.7 7.7 Loss 158172 Thruput * 0.1870.161 4-Carson, 4-Reno CarsonReno Avg Cwnd 8.1 7.0 Loss 90 134 Thruput 0.121 0.109 8-Carson / 8-Reno * Note: Bottleneck bandwidth was 1.5M TCP friendly in all cases Average throughput less than TCP response function for (loss, RTT) combination
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Summary TCP variant (on top of Reno) Detects Steady State Adapts responsiveness Benefits: –Increase throughput –Reduces loss –Reduce window-size variance –End-to-End protocol
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Future Work AIMD action RED/ECN effect Application performance Slow-start, high congestion periods Steady state detection algorithms
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TCP-Carson A Loss-event Based Adaptive AIMD Protocol for Long-lived Flows Hariharan Kannan Advisor: Prof. M Claypool Co-Advisor: Prof. R Kinicki Reader: Prof. D Finkel
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