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Congestion Control for High Bandwidth-Delay Product Networks

D. Katabi (MIT), M. Handley (UCL), C. Rohrs (MIT) – SIGCOMM’02

Presented by Cheng Huang

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Basics of TCP Congestion Control Bandwidth-delay product

Capacity of the “pipe” between a TCP sender and a TCP receiver

Congestion window (cwnd) sender’s estimation of the capacity

Additive Increase and Multiplicative Decrease (AIMD) algorithm no loss: cwnd = cwnd + s loss: cwnd = cwnd – cwnd/2

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Motivations

Inadequacy of TCP, as bandwidth-delay product increases Prone to instability

regardless of AQM schemes Inefficient

Fairness concern TCP tends to bias against long RTT flows

Satellite links, wireless links, etc.

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Design Rationale

NOT an end-to-end approach Using precise congestion signaling Decoupling efficiency and fairness control

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Features of XCP (eXplicit Control Protocol) Maintains high utilization, small queues, and

almost no drops, as bandwidth/delay increases drop: less than one in a million packets

Maintains good performance in dynamic environment (with many short web-like flows)

No bias against long RTT flows

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XCP – Sender/Receiver’s Role

Sender Fill the congestion header Update cwnd = max(cwnd + H_feedback, s)

Receiver Copy H_feedback to ACK

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XCP – Router’s Role

Control Interval Estimation Average RTT

Efficiency Control Maximize link utilization

Fairness Control Achieve fairness among individual flows

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Control Interval Estimation

Estimation requirement Core stateless Average over flows (not over packets) e.g. two flows have RTTs of 80 ms and 40 ms and

the same cwnd = 10 packets, then average RTT over packets is:

RTTavg = (80*10+40*20)/(10+20) = 53.33 (ms)

Instead, average RTT over flows is:RTTavg = (80*80*10+40*40*20)/(80*10+40*20) = 60 (ms)

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Control Interval Estimation (2)

Weight of each packet wi = H_rtti * (si / H_cwndi)

Average RTT sum(wi * H_rtti) / sum(wi)

Average cwnd sum(wi * H_cwndi) / sum(wi)

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Efficiency Controller (EC)

Aggragate feedback (total H_feedback)

alpha, beta: constant value d: control interval (average RTT) S: spare bandwidth Q: persistent queue size

Stability requirement determinesalpha = 0.4; beta = 0.226

Independent of delay, capacity and number of flows

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Fairness Controller (FC)

Achieve fairness via AIMD algorithm phi > 0, equal throughput increment of all flows phi < 0, throughput decrement proportional to its c

urrent throughput Positive feedback

(1/wi) * (pi/H_rtti) = C1 (constant value) sum(pi/H_rtti) = phi/d

Negative feedback (1/wi) * (ni/H_rtti) = C2 * H_cwndi/H_rtti

sum(ni/H_rtti) = phi/d

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Fairness Controller (FC) (2)

Bandwidth shuffling h = max(0, gamma*y - |phi|)

gamma = 0.1 y: input traffic

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Performance Evaluation

Simulation topology I

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Performance Evaluation (2)

Simulation topology II

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The dynamics of XCP (I)

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The Dynamics of XCP (II)

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Differential Bandwidth Allocation

Replace FC phi > 0: allocate throughput increment according to flows’ prices

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Gradual Deployment – A TCP-friendly XCP Separate queues to distinguish TCP and XCP

traffics Calculate average cwnd of TCP traffics by

Update weights to make TCP and XCP fair

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Conclusion

XCP provides a theoretically sound, yet effective approach to congestion control. It remains excellent performance, independent of link capacity, delay and number of flows.