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Transport Protocols and Congestion Control

Manual: General · Subject: Networking

Examine end-to-end transport, reliability, and congestion-control algorithms from TCP to learned controllers.

From Reliability to Throughput

Transport Functions

Transport protocols provide multiplexing, reliability, ordering, flow control, and congestion control. Their design balances latency, bandwidth efficiency, robustness, and fairness across competing flows.

TCP as a Feedback System

Classic TCP increases sending rate cautiously and reduces it when loss or delay indicates congestion. Its dynamics can be modeled using control theory, where the congestion window acts like a control variable and queue occupancy provides feedback.

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Why Loss Is Ambiguous

Packet loss may reflect congestion, corruption, wireless interference, or policy drops. Interpreting signals correctly is central to transport design.

Transport Design Axes

AxisExamples
ReliabilityARQ, FEC, selective acknowledgments
Congestion signalingLoss, delay, explicit marks
OrderingIn-order delivery, partial ordering
MultiplexingPer-flow, per-connection, multiplexed streams

What is the main purpose of congestion control?

Why is transport often studied as a control problem?

Modern Transport Directions

Recent research includes low-latency congestion control, model-based algorithms, QUIC transport evolution, multipath transport, and learned controllers that adapt to workload and network conditions.

Which signal is often used by modern congestion controllers in low-latency designs?

State one challenge in designing multipath transport.

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Seminal Theme

The enduring question is how a distributed transport protocol can be both efficient and fair when each sender sees only partial, noisy feedback.