Performance Enhancement of TFRC in Wireless Ad Hoc Networks

Mingzhe Li, Choong-Soo Lee, Emmanuel Agu,

Mark Claypool and Bob Kinicki

Computer Science Department

Worcester Polytechnic Institute

Worcester, Massachusetts

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OutlineOutline

Introduction Background TFRC Performance over Wireless

Networks RE-TFRC Algorithm Performance Evaluation Conclusions and Future Work

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IntroductionIntroduction The objective is improved support for streaming

multimedia applications over wireless networks. The TCP Friendly Rate Control protocol (TFRC) was

designed for wired networks. It can perform poorly over wireless networks.

The 802.11 MAC layer wireless protocol uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) and Request-to-Send/Clear-to-Send (RTS/CTS) to avoid frame collisions.

TFRC performance suffers from the contention delays and drops known as RTS/CTS jamming and RTS/CTS-induced congestion.

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IntroductionIntroduction This paper introduces a wireless extension to

the TFRC protocol, Rate Estimation TFRC (RE-TFRC), that accounts for MAC layer saturation to select a sending rate that outperforms TFRC.

The goal of RE-TFRC is to reduce MAC layer loss rates and collisions and thereby lower transport layer delays with minimal effect on throughput.

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OutlineOutline

Introduction Background TFRC Performance over Wireless

Networks RE-TFRC Algorithm Performance Evaluation Conclusions and Future Work

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TCP Friendly Rate Control (TFRC) [Floyd00]– Designed for streaming media applications– Uses rate-based congestion control and– The TCP Friendly congestion response function:

TFRC is implemented in the Linux kernel as one of the congestion control options of the Datagram Congestion Control Protocol (DCCP).

TCP Friendly Rate Control (TFRC)TCP Friendly Rate Control (TFRC)

83

)321((33

2 2 bpptp

bpr

sX

rto

X: Transmission rate s: packet sizer: round trip time p: lost event ratetrto:: Retransmission time out b: num of packets in each ack

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Hidden Terminal ProblemHidden Terminal Problem

Node 1 is hidden from Node 3:– Node 1 and node 3 cannot sense each other’s

transmissions.– If Node 1 and node 3 transmit at the same time to

node 2, a collision occurs at node 2.– Node 1 and node 3 back off and retransmit.

1 2 3

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Hidden Terminal ProblemHidden Terminal Problem

802.11 Solution to the Hidden Terminal Problem– Use a four-way handshake: RTS-CTS-DATA-ACK where the

RTS and CTS packets are significantly smaller than the average data packet.

– The maximum number of RTS retransmissions is set to 7.

However, the 802.11 protocol will still have problems if the MAC layer becomes saturated!!

1 2 3

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MAC Layer SaturationMAC Layer Saturation

MAC layer congestion– The wireless network traffic load is increased

above the MAC layer saturation point. – Contention delays and drops are increased.– The RTS/CTS jamming is hidden from upper layers.

TFRC then computes an ineffective RTT (Round Trip Time) and loss event rate.

This implies a TCP Friendly sending rate that is too high for optimal performance.

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OutlineOutline

Introduction Background TFRC Performance over Wireless

Networks RE-TFRC Algorithm Performance Evaluation Conclusions and Future Work

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TFRC Performance InvestigationTFRC Performance Investigation NS-2 simulations are used. Evaluate a single flow, 802.11b MAC layer protocol over a chain topology

with a 2 Mbps wireless capacity. The throughput decreases as the number of hops increases.

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Rate Constrained TFRCRate Constrained TFRC A seven-hop chain network was simulated. The TFRC sending rate is manually constrained. The MAC layer saturates at 300Kbps.

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Rate Constrained TFRCRate Constrained TFRC The TFRC loss event rate and RTT increase sharply

after a 300Kbps constrained sending rate. Thus, unconstrained TFRC runs in a sub-optimal

state due to MAC layer congestion.

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OutlineOutline

Introduction Background TFRC Performance over Wireless

Network RE-TFRC Algorithm Performance Evaluation Conclusions and Future Work

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Rate Estimation TFRC (RE-TRFC)Rate Estimation TFRC (RE-TRFC)

RE-TFRC estimates the optimum sending rate based on:

– The number of hops in the flow path– The current loss event rate.

The TFRC sending rate is adjusted depending on the estimate of the optimum sending rate.

RE-TFRC preserves the ceiling imposed by the TCP Friendly sending rate.

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Rate EstimationRate Estimation

Rate Estimate in TCP Westwood [wang02]– Upon congestion, Westwood sets the TCP

window size to

W = Bit-rateest * rttmin

– rttmin is the smallest recorded rtt, i.e., an estimate of latency.

RE-TRFC Rate Estimate Approach– Estimate the optimum sending rate that will not

saturate the MAC layer.

– Determine the MAC layer saturation rtt: rttopt

– Control the sending rate on congestion.

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TCP Friendly equation:

Inverse TCP function:

X: TCP Friendly rate

p: TFRC loss event rate

RE-TFRC Rate EstimationRE-TFRC Rate Estimation

Use R to estimate p’

Use p’ to estimate R’

),( prttfX

),( Xrttfp

),(' Rrttfp opt

)',(' prttfR cur

R: TFRC estimated receiving rate

p’: Adjusted TFRC loss event rate

R’: Estimated optimum sending rate

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Single hop delay model: [Carvalho03]

Multi-hop chain delay model:– Divide the N-hop chain into N-2 4-node networks

and two 3-node networks.– Sum the data/ack packet delay over the N hops.

Round Trip Time ModelingRound Trip Time Modeling

timebackoff average :

timensmission packet tra :

B

s

sB

T

t

tTT

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Round Trip Time ModelingRound Trip Time Modeling

1 2 3 4 5

)4()2()3(2)4()2()3(2

00

ackackdatadata

N

iack

N

idata

TNTTNT

TTNrii

: estimate of rttopt for N-hop chain topology

: Single hop delay of Ack packet

: Single hop delay of Data packet

)(Nr

ackT

dataT

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Rate Estimation TFRC AlgorithmRate Estimation TFRC Algorithm

On receiving an ack:1. Compute R (the original TCP Friendly rate) .2. Estimate rttopt. using the r(N) approximation.

[Assume N can be obtained from the routing protocol.]

3. Compute the adjusted loss event rate p’ using rttopt and R.

4. Compute the estimated optimum send rate R’.5. Use the original rate, R, if the new rate, R’, is

larger.6. If there is a rate change, make the change

incrementally as TFRC does.

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OutlineOutline

Introduction Background TFRC Performance over Wireless

Network RE-TFRC Algorithm Performance Evaluation Conclusions and Future Work

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Simulation DetailsSimulation Details NS-2 was used to simulate and evaluate

RE-TFRC performance. Wireless Multi-hop Chain Network

– N-hop network implies N+1 nodes (n0 to nN).

– All simulated TRFC flows go from n0 to nN.– The number of hops in the chain network

was varied from 4 to 15.– The bit err rate (BER) was varied from 10-6

to 10-4.

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Seven-Hop Chain TopologySeven-Hop Chain Topology

CDF of MAC layer retransmissions

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Loss Event Rate for Multi-Hop ChainsLoss Event Rate for Multi-Hop Chains

Average loss event rate versus number of hops

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Average round trip time versus number of hops

Round Trip Times for Multi-Hop ChainsRound Trip Times for Multi-Hop Chains

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Throughput for Multi-Hop ChainsThroughput for Multi-Hop Chains

Average throughput versus number of hops

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Average loss event rate for various flow scenarios

Loss Event Rate for Multi-Flow TestsLoss Event Rate for Multi-Flow Tests

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Average round trip time for various flow scenarios

Round Trip Time for Multi-Flow TestsRound Trip Time for Multi-Flow Tests

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Throughput for Multi-Flow TestsThroughput for Multi-Flow Tests

Average throughput for various flow scenarios

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Bit Error Rate Test of RE-TFRCBit Error Rate Test of RE-TFRC

BER 10-6 10-5 10-4

RTT Reduction 39% 32% 14%Loss Rate Reduction 55% 45% 29%

Throughput Improvement 6.5% 4.2% 0.5%

Single flow, seven-hop chain topology

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OutlineOutline

Introduction Background TFRC Performance over Wireless

Networks RE-TFRC Algorithm Performance Evaluation Conclusions and Future Work

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ConclusionsConclusions Rate Estimation TFRC (RE-TFRC)

– Estimates MAC layer saturation and controls the TFRC sending rate.

– Lowers the delay and loss rate and can even increase throughput in most cases:

• Lowers round-trip time up to 40%• Lowers loss event rate up to 80%• Increases throughput up to 5%.

– reduces MAC layer congestion.

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Future WorkFuture Work

Extend Algorithm:– To other topologies: cross, grid, and

random– Consider mobile nodes.

Incorporate into applications– Such as streaming multimedia

Implement TFRC wireless extension in Linux.

Thanks!

rek@cs.wpi.edu