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Advanced Transport Protocol Design

Advanced Transport Protocol Design. Nguyen Nguyen Multimedia Communications Laboratory March 23, 2005. Outline. Introduction Overview of TCP/IP System model Queueing model for congestion Loss discrimination Modified AIMD Future work. Introduction. Transport protocol

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Advanced Transport Protocol Design

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  1. Advanced Transport Protocol Design Nguyen Nguyen Multimedia Communications Laboratory March 23, 2005

  2. Outline • Introduction • Overview of TCP/IP • System model • Queueing model for congestion • Loss discrimination • Modified AIMD • Future work

  3. Introduction • Transport protocol • End-to-end data transmission • Sequencing, flow control, congestion control etc. • Transport protocol measures of performance • Throughput (bytes/second) • Fairness • Latency • TCP-friendliness

  4. Introduction (2) • Goal: design a reliable transport protocol that achieves high throughput and fairness • Key: congestion control • Congestion control design • Congestion detection (loss discrimination) • Response to congestion

  5. Overview of TCP/IP • Layered network architecture

  6. Overview of TCP/IP (2) • Internet Protocol (IP) • End-to-end data transmission • Routing • Best-effort • User Datagram Protocol (UDP) • Basically raw IP • Fast, but unreliable

  7. Overview of TCP/IP (3) • Transmission Control Protocol (TCP) • Connection-oriented • Not as fast as UDP, but reliable • Sliding window transmission policy

  8. Overview of TCP/IP (4) • Reliability through retransmission • Retransmit lost packets (triple duplicate ACK or timeout) • Flow control • Buffer advertisements from the receiver • Congestion control • Congestion indicator = packet loss

  9. Overview of TCP/IP (5) • Additive increase, multiplicative decrease (AIMD) Additive increase Timeout Window Triple-duplicate ACK Slow-start Time (RTT)

  10. Overview of TCP/IP (6) • Problem 1. Inaccurate congestion indicator • Packet loss in wireless networks is mainly due to random transmission error (i.e. fading) • Problem 2. Response to congestion • TCP is too conservative because it does not have an up to date notion of the available bandwidth

  11. System model • Network model Internet destination1 source1 MH BS destination2 source2 MH

  12. System model (2) • Adjust the rate of the sender subject to the following constraints • Hybrid wired/wireless network topology • No help from intermediate routers • Unsynchronized clocks • Online

  13. Queueing model • Single-server queueing system • Customer: packet from primary source plus preceding cross-traffic Primary flow Cross-traffic

  14. Queueing model (2) • {X2, X3, …} - sequence of interarrival times • {S1, S2, …} - sequence of service times • {Q(t) : t ≥ 0} - number of customers in queue • Traffic intensity: ratio of average service time to average interarrival time

  15. Queueing model (3) • D/G/1 queueing system • Case 1: Independent, identically distributed (IID) service times • {S1, S2, …} is a sequence of IID r.v.’s • Theorem 1. Let Dn be the departure time of the nth customer. Then {Q(Dn) : n ≥ 1} is a Markov chain.

  16. Queueing model (4) • Proof. Let Un be the number of customers arriving during the service time Sn+1 of the (n+1)th customer. But Un = T-1Sn+1 and service times are independent.

  17. Queueing model (5) • Case 2: Dependent service times • {S1, S2, …} is a stationary, ergodic process • {Q(Dn) : n ≥ 1} is not a Markov chain • Theorem 2 [Grimmett]. The waiting time distribution, P(W ≤ w), is non-defective if • (a) ρ < 1, or • (b) ρ = 1 and Var(S – X) = 0.

  18. Queueing model (6) • Long-term properties • Average number of customers in the system • Average number of customers in queue, average delay through the system, average waiting time can also be derived

  19. Loss discrimination • Improved congestion detection • Packet loss • Delay • Theorem 2: Long-term stability achieved if average service rate > average arrival rate • The long-term does not exist in our problem

  20. Loss discrimination (2) • Sample traffic intensity • Step 1. Calculate the “short-term” average over a time interval

  21. Loss discrimination (3) • Condition 1. If > 1 and increasing trend of traffic intensity is observed, congestion ifthen congestion_loss endif

  22. Loss discrimination (4) • Condition 2. If a large, sudden spike in traffic intensity is observed, congestion ifthen congestion_loss endif

  23. Loss discrimination (5) • Step 2. Communicate cause of loss to the sender via a feedback message. • Step 3. Retransmit. If cause of loss was congestion, sender adjusts its rate

  24. Modified AIMD • Maintain up to date estimate of bandwidth • Sample bandwidth • Step 1. Calculate smoothed average

  25. Modified AIMD (2) • Step 2. Communicate bandwidth estimate to sender via feedback message. • Step 3. Set sending window accordingly • Step 4. Additive-increase.

  26. Future work • Reliability through forward error correction (FEC) instead of retransmission • LDPC code • Interleaver • Congestion avoidance instead of AIMD

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