VANET Analysis

Integrity-Oriented Content Transmission in

Highway Vehicular Ad Hoc Networks

Tom Hao Luan‡, Xuemin (Sherman) Shen‡, and Fan Bai§

‡BBCR, ECE, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada

§ECI Lab, General Motors Global R&D, Warren, MI 48105, USA

1

Outline

Content Transmission in VANETIntroductionProblem Statement

Integrity-Oriented Content Transmission in Highway Vehicular NetworksSystem ModelAnalytical FrameworkCall Admission ControlSimulation Verification

Conclusion

2

Content Transmission

I Digitalized information is always transformed into certain form ofcontent files, of the heterogeneous sizes, for storage andtransmissions

I Text contents: email, social blogs, etc.I Video/audio contents: movie trailers, MP3 music files, etc.

I Infotainment applications in VANET typically boil down to theconsecutive transmissions of the different types of content files

I Social communications with images, texts and video/audio cliptransmission

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Integrity of Content TransmissionI Content files need to be transmitted in their entirety so as to guarantee

the successful presentation by the on-top application at the receiverI Downloads stuck at 99% is annoying to BitTorrent usersa

I Content transmissions over VANET are susceptible to frequentinterruptions due to the dynamic motilities

1. Content transmissions take time to finish2. The inter-vehicular connections tend to be short-lived

I This leads to fragment contents that are partially transmitted onlyduring the connection time

1. Annoying to end-hosts causing wait but failure of media playout2. Waste the precious VANET bandwidth

e.g., transmission of

a 3MB file over a

300kbps connection

takes 82 seconds

aTorrentFreak, How to Bring Dead Torrents Back to Life

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Problem StatementI Given the size of a content file to be transmitted and the density of

vehicles on the road, we question onI how likely the file can be transmitted successfully, andI how to guarantee the integrity of the content transmissions

I We propose the integrity-oriented content transmission framework inVANET which is composed of

1. Analytical framework to evaluate the data volume that can betransmitted from sender to receiver within a given period of time

2. Admission control to filter suspicious transmission requests whichare unlikely to be finished over the transient inter-vehicle connectiontime

I AssumptionsI Single-hop transmissions:

multi-hop can be future workI No multi-party download

Throughput? Safe to transmit ?

5

System Model

I Highway vehicular networksI Vehicles move along a linear topology

Vehicle i (sender) Vehicle j

(receiver)

File size Fij

I Investigate on content transmissions between a random selected pairof vehicles i (sender) and j (receiver)

I Let R(t) denote the transmission throughput from i to j at time t

I Let A(Υ) =∫ Υ

0 R(t)dt denote the data volume that can betransmitted within a time period of Υ

I Provided Υ and content file size Fij to transmit, our goal is to

1. derive the expression of A(Υ)2. evaluated the likelihood that A(Υ) > Fij

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Analytical Framework

I At time t = 0, the evaluation is performed

I We perform the following 4 steps

Download subscription submitted at t = 0

0

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Analytical Framework

I At time t = 0, the evaluation is performed

I We perform the following 4 steps

At time tEstimate headway

distance1

Download subscription submitted at t = 0

0

8

Analytical Framework

I At time t = 0, the evaluation is performed

I We perform the following 4 steps

At time tEstimate headway

distance1

2 Evaluate physical-layer capacity (function of distance)

Download subscription submitted at t = 0

0

9

Analytical Framework

I At time t = 0, the evaluation is performed

I We perform the following 4 steps

At time tEstimate headway

distance1

2 Evaluate physical-layer capacity (function of distance)

3 MAC throughput (function of physical-layer capacity)

Download subscription submitted at t = 0

0

10

Analytical Framework

I At time t = 0, the evaluation is performed

I We perform the following 4 steps

At time tEstimate headway

distance1

2 Evaluate physical-layer capacity (function of distance)

3 MAC throughput (function of physical-layer capacity)

Download subscription submitted at t = 0

4Evaluate download volume as

throughput integrated over time

0

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Headway DistanceI Let H(t) denote the headway distance from i to j at time t

I H(t) ≥ 0 if i is ahead of j in the moving direction, otherwise, H(t) < 0I Let vi (resp. vj) and ai (resp. aj) denote the mean and variance, respectively, of

the velocity of vehicle i (resp. j)I We model H(t) as the queue length of a G/G/1 queue in the unit of meter

I We resort to the diffusion approximation to obtain the pdf of H(t) over time tI The headway distance H(t) is modeled to follow the Wiener process, i.e., within

the infinitesimal interval ∆t, the increment of H is normally distributed as

∆H (t) = H (t + ∆t)−H (t) = µ∆t + Θ√

σ∆t

where µ = vj − vi and σ = aj + aj

,

, , ,

G/G/1

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Headway Distance (cont’d)I Let fH (x; r, t) denote the probability density function (pdf) of H (t) at time t,

conditional on the initial queue length, and

fH (x; r, t) = Pr{x ≤ H (t) ≤ x + ∆x| H (0) = r}.

where r denotes the initial headway distance, i.e., H(0)I fH (x, r, t) can be characterized by the Kolmogorov equation (alternatively known

as Fokker–Planck equation) as

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σ∂2

∂x2 fH (x; r, t) + µ∂

∂xfH (x; r, t) =

∂

∂tfH (x; r, t)

subject to the initial condition of the headway distance,

fH (x; r, 0) = δ (r) ,

I According to [1], we have

fH (x; r, t) =1√

2πσtexp

{− (x− r− µt)2

2σt

}[1] D. R. Cox and H. D. Miller, The Theory of Stochastic Processes. Chapman & Hall/CRC, 1977

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Physical-layer Transmission Rate

I Let C(t) denote the physical-layer transmission rate from i to jI C(t) is dependent on H(t)

I C(t) is subjected to the fast channel fadings from i and jI We adopt the model in [2, 3] to derive the expression of C(t), which

is represented by H(t)I Ref. [2] characterizes the fast channel fading between two vehiclesI Ref. [3] provides a model to evaluate the capacity with multiple

modulation rates applied

[2] L. Cheng, B. E. Henty, D. D. Stancil, F. Bai, and P. Mudalige, “Mobile Vehicle-to-VehicleNarrow-band Channel Measurement and Characterization of the 5.9 GHz Dedicated ShortRange Communication (DSRC) Frequency Band,” IEEE Journal on Selected Areas inCommunications, vol. 25, no. 8, pp. 1501 - 1516, Oct. 2007.

[3] J. Yoo, B. S. C. Choi, and M. Gerla, “An Opportunistic Relay Protocol for VehicularRoad-side Access with Fading Channels,” in Proc. of IEEE ICNP, 2010.

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MAC ThroughputI The MAC throughput represents the effective transmission rate from i to j with

channel contentions taken into considerationI We assume that the fundamental DCF MAC with RTS/CTS handshake is

applied to schedule the channel access of nodes

I Let N denote the number of vehicles contending for the transmission with iI N follows the Poisson distribution with known mean value

I Let τ denote the transmission probability of each vehicleand

τ =1

W/2 + 1where W is the minimum contention window size

I The MAC throughput R is evaluated as

R (t) =τPsucFLiT

where Psuc is the successful transmission probability. FLi is the frame length of i. Tis the average length of a time slot (where C (t) comes into play)

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Data Volume That Can Be TransmittedI The data volume that can be transmitted within a time period Υ is thus

A(Υ) =∫ Υ

0R(t)dt

I Evaluating A(Υ) with the above equation involves stochastic integralI We evaluate its mean, E (A(Υ)), and the upper-bound of its variance,V(A(Υ)) instead

I Call Admission Control: with file size Fij known,the transmission request is admitted iff

Pr{A(Υ) > Fij

}> ξ

Vehicle i (sender) Vehicle j

(receiver)

File size Fij

I We apply the one-sided Chebyshev inequality to derive a sufficientcondition on E (A(Υ)) and V(A(Υ)) to have above inequality satisfied,with

Pr{A ≤ Fij

}≤ V (A)V (A) +

[E (A)− Fij

]2 ≤ 1− ξ

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SimulationI We evaluate the accuracy of the analysis and effectiveness of the call

admission control scheme using a simulator coded in C++

I We simulate 1000 vehicles on a highway section with mean inter-distance60 meters

I The velocity of vehicles follows the normal distribution with the mean andstandard deviation uniformly selected from [70, 130] km/h and [21, 39]km/h, respectively

I Channel fading between vehicles follows the Nakagami-m distribution withparameters derived in [2]

I Legacy DCF with RTS/CTS handshake is deployed as MAC

Mean 60 meters

[2] L. Cheng, B. E. Henty, D. D. Stancil, F. Bai, and P. Mudalige, “Mobile Vehicle-to-Vehicle Narrow-band ChannelMeasurement and Characterization of the 5.9 GHz Dedicated Short Range Communication (DSRC) Frequency Band,” IEEEJournal on Selected Areas in Communications, vol. 25, no. 8, pp. 1501 - 1516, Oct. 2007.

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Accuracy of AnalysisWe focus on a randomly selected pair of vehicles and report the mean and variance ofits data volume download over time

30 60 90 120 150 180 210 240

0.5

1

1.5

2

2.5

3x 10

7

Simulation Time (in seconds)

Mea

n D

ata

Vol

ume

(in b

ytes

)

AnalysisSimulation

30 60 90 120 150 180 210 240

2

4

6

8

10

12

14

x 1013

Simulation Time (in seconds)V

aria

nce

of D

ata

Vol

ume

AnalysisSimulation

I The analysis of the mean data volume matches the simulations well

I As time increases, the gap between the upper bound of download volume

variance and the simulation increases

I In real-world applications, connection time would be typically short

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Effectiveness of Call Admission Control (CAC)

within [0,100s] within [0,450s]0

0.1

0.2

0.3

0.4

0.5

0.6

Fra

ctio

n of

Fra

gmen

t Con

tent

s

std = 54 km/h, without CACstd = 30.6 km/h, without CACstd = 10.8 km/h, without CACstd = 54 km/h, with CACstd = 30.6 km/h, with CACstd = 10.8 km/h, with CAC

within [0, 100s] within [0, 450s]0

1

2

3

4

5

6x 10

7

Val

id D

ata

Vol

ume

(in b

ytes

)

std = 54 km/h, without CACstd = 30.6 km/h, without CACstd = 10.8 km/h, without CACstd = 54 km/h, with CACstd = 30.6 km/h, with CACstd = 10.8 km/h, with CAC

I With CAC applied, portion of fragment content transmissionsreduces dramatically

I With CAC applied, the download volume of valid contents increasesI Small file size is favored

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ConclusionI The infotainment applications in VANET may boil down to the transmission of

consecutive content files from send to receiver

I The contents need to be transmitted in their entirety so as to be useful to theon-top applications

I Existing literature largely focus on the packet-level performance in throughputand delay of packet transmissions, but neglect the session-level performance interms of the integrity of content transmissions

I Given the mobility statistics of vehicles, we develop a mathematical framework toevaluate the data volume that can be transmitted among a random pair ofvehicles

I Based on the model, we then propose a call admission control mechanism tofilter to suspicious transmission requests

I Future work

I Extend the framework to multi-hop transmissionsI Develop the channel scheduling scheme to guarantee the integrity of

content transmissions

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Thank You!

Slides are available at author’s (Tom H. Luan) website:http://bbcr.uwaterloo.ca/ hluan

Please forward your questions to the author through email:hluan@uwaterloo.ca

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