Overview• Goal: video streaming in

vehicular networks via WiFi

• Compelling usage scenarios– Gas stations and local shops

deploy APs to provide video and ads

– Taxis/buses provide value-added services to passengers

• Cellular networks: costly ($60 for 5GB/month 0.1Mbps for <5 days!); limited bandwidth

Enabling High-Bandwidth Vehicular Content

Distribution

U. Shevade, Y. C. Chen, L. Qiu, Y. Zhang, V. Chandar, M. K. Han, H. H. Song, Y. S. Seung

UT Austin

3

Challenges

• Vehicles move at high speed– WiFi contacts are short and intermittent– 70% contacts less than 10 seconds

• Sparse AP coverage– Dense coverage over large area expensive

• Internet access links to APs are bottleneck– Naïve solution: Download from Internet during

contact– Insufficient b/w if data fetched during contact

Types of Connectivity• AP wireline access: persistent connectivity, but

insufficient BW– Internet-to-AP throughput is 768Kbps-6Mbps (DSL)– Cannot sustain high data rate if data is fetched only

during contact• AP wireless access: high BW, but short-lived

connectivity– Our measurements: AP-to-car throughput is 40-

56Mbps using 802.11n– High vehicular speed short contact (70%

contacts less than 10s)• Wireless mesh network: high BW, but low coverage • Vehicle relay traffic between APs: high BW, high delay• Q: Can we combine multiple types of connectivity to

enable high-bandwidth vehicular content delivery?

5

Synergy among connections

High b/w, short-lived

High b/w, high delay

Low b/w, persistent

High b/w, low coverage

VCDVCD High b/w, persistent

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VCD Architecture

ControllerControllerContent SourceContent Source

Internet

•Download and upload data •Upload GPS location updates, video demands, what car has

•Download and upload data •Upload GPS location updates, video demands, what car has

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Contributions

• New techniques to optimize replication – Goal: Fully utilize wireless bandwidth during contact– Optimize wireline replication to Internet-connected

APs– Optimize mesh replication and use it for cooperative

caching– Replicate using vehicular relays to APs

• New algorithm for mobility prediction– Predict set of APs that will be visited by vehicles

• Critical for success of replication techniques

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Wireline Replication

Controller collects vehicle demands for

interval (i+1) and what content is

present at vehicles and APs

Controller collects vehicle demands for

interval (i+1) and what content is

present at vehicles and APs

Predicts set of APs visited by vehicle in interval (i+1)

Predicts set of APs visited by vehicle in interval (i+1)

Computes what content should be replicated to which APs

Computes what content should be replicated to which APs

Content servers replicate content to APsContent servers replicate content to APs

At start of interval iAt start of interval i

Vehicle downloads content from APs Vehicle downloads content from APs

During interval (i+1)

During interval (i+1)

During interval iDuring interval i

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Optimize Wireline Replication

Interval length, Content present at cars and APs, car demand, AP-to-visit

Interval length, Content present at cars and APs, car demand, AP-to-visit

Content to transfer to APs and content to download to cars Content to transfer to APs and content to download to cars Total content downloaded to cars weighted by interest,

while minimizing the amount of content replicated to APs

Total content downloaded to cars weighted by interest, while minimizing the amount of content replicated to

APs

Total download from AP to car bound by wireless capacityTotal download from AP to car bound by wireless capacity

Per-file download to car bound by the difference between file size and what car already hasPer-file download to car bound by the difference between file size and what car already has

Per-file download to car cannot exceed what AP already has and what is replicated to it from the InternetPer-file download to car cannot exceed what AP already has and what is replicated to it from the Internet

Per-file replication to AP bound by the difference between file size and what AP already hasPer-file replication to AP bound by the difference between file size and what AP already has

Total replication to AP does not exceed Internet access link capacityTotal replication to AP does not exceed Internet access link capacity

For each interval i, compute replication strategy maximizing user satisfaction for interval (i+1)

For each interval i, compute replication strategy maximizing user satisfaction for interval (i+1)

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Contributions• New techniques to optimize replication

– Goal: Fully utilize wireless bandwidth during contact– Optimize wireline replication to Internet-connected

APs– Optimize mesh replication and use it for cooperative

caching– Replicate using vehicular relays to APs

• New algorithm for mobility prediction– Predict set of APs that will be visited by vehicle

• Critical for success of replication techniques

• APs are often close enough to form mesh networks

CDF of total contact duration with AP connected components

Mesh Networks of APs

Substantial contact with APs that can potentially form mesh networks

Substantial contact with APs that can potentially form mesh networks

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San Francisco, 100m range San Francisco, 200m rangeSeattle, 100m range Seattle, 200m range

• Nearby APs can be organized into mesh networks using another wireless card– Replicate content to APs using mesh in addition to Internet link– Fetch missing content from other mesh nodes rather than Internet

• Changes to linear program– Constraint C3:

– Two new constraints:

– Objective function:• Add

Mesh Networks of APs

Per-file download to car cannot exceed what AP already has and what is replicated to it from the Internet and from the meshPer-file download to car cannot exceed what AP already has and what is replicated to it from the Internet and from the mesh

AP cannot replicate more content over mesh than it hasAP cannot replicate more content over mesh than it hasInterference constraint: Total active time of all mesh nodes cannot exceed 100%, assuming all nodes interfere with each other

Interference constraint: Total active time of all mesh nodes cannot exceed 100%, assuming all nodes interfere with each other

Prefer a replication which uses less mesh traffic among the ones supporting equal traffic demandsPrefer a replication which uses less mesh traffic among the ones supporting equal traffic demands 12

13

Contributions• New techniques to optimize replication

– Goal: Fully utilize wireless bandwidth during contact– Optimize wireline replication to Internet-connected

APs– Optimize mesh replication and use it for cooperative

caching– Replicate using vehicular relays to APs

• New algorithm for mobility prediction– Predict set of APs that will be visited by vehicle

• Critical for success of replication techniques

14

Vehicular Replication

• Vehicles act as data relays between APs

• Simple strategy: epidemic dissemination– Vehicle uploads content to AP

• based on expected future demand at AP• AP computes future demand, car notifies what it has• AP requests content from the car

– Vehicle downloads content from AP• First the files it is interested• In remaining time, download content randomly

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Mobility Prediction

• Predict which APs a car will meet in next interval

• Challenges:– Vehicles move at high speeds– GPS location updates from vehicles

• Low frequency• Irregular updates

– Road and traffic conditions highly dynamic

• Previous work: 1st and 2nd order Markov models– Do not perform well on our dataset

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Voting among K Nearest Trajectories

• Exploit history to predict contact:

Vehicle’s near history

Vehicle’s near history

Past trajectories from other vehicles

Past trajectories from other vehicles

•Find K trajectories that most closely match the vehicle’s recent history•Obtain future path for K trajectories• Report all APs visited by at least T of K trajectories

•Find K trajectories that most closely match the vehicle’s recent history•Obtain future path for K trajectories• Report all APs visited by at least T of K trajectories

#Correctly predicted APs#Total predicted APs

• Setup: Gas stations as APs, radio range = 200m, prediction interval 3min

1200 Seattle city buses

Mobility Prediction Results

Voting among K nearest trajectories performs best for our dataset

Voting among K nearest trajectories performs best for our dataset

#Correctly predicted APs#Total APs actually visited

( 2 )

(1/precision+1/recall)

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Bus mobility is more

predictable

500 San Francisco Yellow Cabs

UDP with congestion

control

UDP with congestion

control

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VCD Implementation

ControllerController

Coordinator LP Server

Content serversContent servers

802.11b APs802.11b APs

802.11n APs802.11n APs

Ethernet

C++ on Linux

C++ on Linux

TCP for control messages, UDP for dataTCP for control messages, UDP for data

HP iPaq, HTC TiltHP iPaq, HTC Tilt

C# on Windows Mobile 6.1

C# on Windows Mobile 6.1

Dell, Macbook Pro

Dell, Macbook Pro

C# on Windows XP

C# on Windows XP

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802.11b Testbed• 14 APs deployed in 8 campus buildings

– APs are in-building, 20-60ft from the road– 802.11b radios with fixed data rate of 11Mbps– 3 APs in ACES form a mesh network– Smartphone clients stream H.264 videos at 64Kbps

11

22

33 44

55667,8,9,1

0, 11,12

7,8,9,10,

11,1213, 1413, 14

802.11n Testbed• 802.11n is the new WLAN standard

– Considerable throughput increase over 802.11b/g– Uses MIMO and 20/40MHz channels

• Vehicular throughput experiments

– Considerable potential throughput increase over 11b

• Deployed four 802.11n APs– Laptops used as clients

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802.11b 4.6Mbps

802.11g 22.2Mbps

802.11n, 2.4GHz 39.7Mbps

802.11n, 5GHz 56.1Mbps

APs: Gas stations, 100m range

Results – Simulation• Setup: 50 cars, Zipf-like demands, 50% APs not connected to

Internet

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APs: Coffee Shops, 100m range

Internet is the bottleneck

Benefit from wireline replication

Wireless replication

helps!

Wireline+wireless5.2X baseline

6.3X better than baseline

VCD achieves higher throughput by combining wireline, wireless and mesh replication

VCD achieves higher throughput by combining wireline, wireless and mesh replication

Mesh adds 3-13%

Results – Simulation• Setup: 50 cars, Zipf-like demands, 50% APs not connected to

Internet

22

APs: Coffee Shops, 100m range

Mesh benefits 14-20%

Benefits increase with higher range and dense AP deployment

Benefits increase with higher range and dense AP deployment

APs: Coffee shops, 200m range

Low

Medium

High

Video quality over 3G

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Emulab: Simulator Validation

Simulator results within 10% of Emulab resultsSimulator results within 10% of Emulab results

All APs connected to Internet 10% APs connected to Internet

• Setup: 30 APs, 100 cars, 200m range

• 802.11b testbed: 8 APs, 3 connected by mesh

• 802.11n testbed: 4 APs, all connected by mesh

Results - Testbed

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Download (kB)

Play time (sec)

No replication 29297 3662

Wireline 71930 8991

Wireline + Mesh

79440 9930

Full replication 92493 11562

Download (kB)

Play time (sec)

No replication 16857 2107

Wireline 123175 15387

Wireline + Mesh

130827 16353

Full replication 136479 17060

2.7X

7.8X

Summary: Vehicular Content Distribution

• KNT: A new mobility prediction algorithm – Based on voting among K nearest trajectories– 25-94% more accurate than 1st and 2nd order Markov models

• A series of novel replication schemes – Optimized wireline replication and mesh replication – Opportunistic vehicular relay based replication

• Extensive evaluation: simulation + testbed + emulation– Simulation using San Francisco taxi and Seattle bus traces

• 3-6x of no replication, 2-4x of wireline or vehicular alone– Full-fledged prototype deployed on two real testbeds

• 14-node 802.11b testbed and 4-node 802.11n testbed• 4.2-7.8x gain over no replication

– Emulab emulation with real AP/controller and emulated vehicles• Show system works at scale and is efficient• Validate our trace-driven simulator