UNIVERSITY OF MASSACHUSETTS, AMHERST • Department of Computer Science

Anticipatory Wireless Bitrate Control for Blocks

Xiaozheng Tie, Anand Seetharam, Arun Venkataramani, Deepak Ganesan,

Dennis Goeckel

University of Massachusetts Amherst

UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science 2

Wireless bitrate control

Goal: To optimize goodput by adapting effective sending rate to channel quality

Data packet

Channel feedback

6Mbps

1Mbps

2Mbps

Badchannel

Goodchannel

Goodchannel

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Blocks reduce overhead

Blocks = Large batch of packetsE.g., 64KB MAC block in 802.11n1MB block in Hop transport [NSDI’09]

Packet

Ack

DIFSBackoff

SIFSX

X

Packet transmission

DIFSBackoff

XX

Block transmission

SIFSTimeout

BackoffDIFS

Backoff

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Responsiveness vs. overhead

6Mbps

1Mbps

2Mbps

X

XX

Block transmission Low responsiveness Low overhead

6Mbps6Mbps6Mbps6Mbps6Mbps6Mbps6Mbps

Packet bitrate control High responsiveness High overhead

Can we have both high responsiveness and low overhead?

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Outline

Why anticipatory bitrate control BlockRate design and implementation EvaluationConclusion

UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science

Overhead vs. responsiveness (1)

Overhead matters more in static settings

6

(Packet-based)(Block-based)(Block-based)

1.6x

[Mobisys’08]

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Overhead vs. responsiveness (2)

Both overhead and responsiveness matter in mobile settings

30mphData

2x 6Mbps

6Mbps6Mbps6Mbps

6Mbps6Mbps12Mbps12Mbps

12Mbps

Charm+Block Oracle+Block

1.7x

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Outline

Why anticipatory bitrate control BlockRate design and implementation EvaluationConclusion

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Anticipatory bitrate control

Anticipatory = Selecting multiple bitrates predictive of future channel conditions.

Bitrate control for packets

6Mbps

Anticipatory bitrate control for blocks

6Mbps

12Mbps

Goodchannel

6Mbps

6Mbps

6Mbps

6Mbps

12Mbps

12Mbps

12Mbps

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Predict SNR trend: Slow-changing

Linear regression modelAssumes SNR linearly varies with time in slow-changing scenarios

StaticPedestrian (1m/s)

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Predict SNR trend: Fast-changing

Path loss modelAssumes SNR logarithmically varies with distance in fast-changing scenarios

30mphSNR(d)= SNR(d0) – 10αlog(d/d0)

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BlockRate design summary

30dB

40dB

6Mbps

6Mbps

12Mbps

12Mbps

2. Lookup SNR-Bitrate table to select anticipatory bitrate

1. Predict future SNR based on mobility pattern

SNR Bitrate

… …

40dB 12Mbps

… …

Linear regression

Path loss

Slow mobility

?

YesNo

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SNR-Bitrate table

Maintains bitrate that maximizes goodput at each SNR

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Outline

Why anticipatory bitrate controlBlockRate design and implementation EvaluationConclusion

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Experimental setup

Vehicular Pedestrian Static

V-to-V: 20 buses

V-to-AP: 2 cars

Mesh:16 MacMini nodes2 mobile laptops

ns3 simulation

Pedestrian

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Performance in V2V testbed

BlockRate Charm+Block Charm SampleRate

#V2V contacts

1745 1822 1524 1719

1.3x

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Performance in V-to-AP testbed

30mph

Data

1.6x

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Performance in pedestrian mobility

Pedestrian mobility trace-driven simulation in ns-3

(Uses PHY-hint) (Uses movement-hint)

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Conclusion

State-of-the-art bitrate control schemes must pick one: low overhead or high responsiveness

BlockRate achieves both benefits Anticipatory bitrate control using blocks reduces overhead while being responsive

Thank you!