Advanced Transport Protocol Design

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

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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 - PowerPoint PPT Presentation

Transcript of Advanced Transport Protocol Design

Page 1: Advanced Transport Protocol Design

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Advanced Transport Protocol Design

Nguyen Nguyen

Multimedia Communications Laboratory

March 23, 2005

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Outline

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

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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

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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

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Overview of TCP/IP

Layered network architecture

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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

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Overview of TCP/IP (3)

Transmission Control Protocol (TCP) Connection-oriented Not as fast as UDP, but reliable

Sliding window transmission policy

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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

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Overview of TCP/IP (5)

Additive increase,

multiplicative decrease (AIMD)

Additive increase

Triple-duplicate ACK

Timeout

Slow-start

Win

dow

Time (RTT)

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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

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System model

Network model

source1

Internet

source2

destination1

destination2

BS

MH

MH

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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

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Queueing model

Single-server queueing system

Customer: packet from primary source plus preceding cross-traffic

Cross-traffic

Primary flow

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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

][

][

XE

SE

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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.

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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.

0)(

0)(1)()(

1 DQUDQDQU

DQnn

nnn

n if

if

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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.

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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

2

][

])[1(2

)(][

1

1

2 SET

SET

SVarTQE

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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

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Loss discrimination (2)

Sample traffic intensity

Step 1. Calculate the “short-term” average over a time interval

tt ii

ii

i1

1

N

i

s

i

s

N 1

)()( 1

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Loss discrimination (3)

Condition 1. If > 1 and increasing trend of traffic intensity is observed, congestion

if then

congestion_loss

endif

)(s

)()(

Ms

K

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Loss discrimination (4)

Condition 2. If a large, sudden spike in traffic intensity is observed, congestion

if then

congestion_loss

endif

)( 1 Mii

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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

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Modified AIMD

Maintain up to date estimate of bandwidth Sample bandwidth

Step 1. Calculate smoothed average

bbb iii)1(

1 1,0,

1

_

ii

i

sizepacketb

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Modified AIMD (2)

Step 2. Communicate bandwidth estimate to sender via feedback message.

Step 3. Set sending window accordingly

Step 4. Additive-increase.

sizesegment

RTTbwindow

_

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Future work

Reliability through forward error correction (FEC) instead of retransmission LDPC code Interleaver

Congestion avoidance instead of AIMD