Integrity-Oriented Content Transmission in Highway Vehicular Ad Hoc Networks

Transcription

1 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

2 Outline Content Transmission in VANET Introduction Problem Statement Integrity-Oriented Content Transmission in Highway Vehicular Networks System Model Analytical Framework Call Admission Control Simulation Verification Conclusion 2

3 Content Transmission Digitalized information is always transformed into certain form of content files, of the heterogeneous sizes, for storage and transmissions Text contents: , social blogs, etc. Video/audio contents: movie trailers, MP3 music files, etc. Infotainment applications in VANET typically boil down to the consecutive transmissions of the different types of content files Social communications with images, texts and video/audio clip transmission 3

4 Integrity of Content Transmission Content files need to be transmitted in their entirety so as to guarantee the successful presentation by the on-top application at the receiver Downloads stuck at 99% is annoying to BitTorrent users a Content transmissions over VANET are susceptible to frequent interruptions due to the dynamic motilities 1. Content transmissions take time to finish 2. The inter-vehicular connections tend to be short-lived This leads to fragment contents that are partially transmitted only during the connection time 1. Annoying to end-hosts causing wait but failure of media playout 2. Waste the precious VANET bandwidth e.g., transmission of a 3MB file over a 300kbps connection takes 82 seconds a TorrentFreak, How to Bring Dead Torrents Back to Life 4

5 Problem Statement Given the size of a content file to be transmitted and the density of vehicles on the road, we question on how likely the file can be transmitted successfully, and how to guarantee the integrity of the content transmissions We propose the integrity-oriented content transmission framework in VANET which is composed of 1. Analytical framework to evaluate the data volume that can be transmitted from sender to receiver within a given period of time 2. Admission control to filter suspicious transmission requests which are unlikely to be finished over the transient inter-vehicle connection time Assumptions Single-hop transmissions: multi-hop can be future work No multi-party download Throughput? Safe to transmit? 5

6 System Model Highway vehicular networks Vehicles move along a linear topology Vehicle i (sender) File size F ij Vehicle j (receiver) Investigate on content transmissions between a random selected pair of vehicles i (sender) and j (receiver) Let R(t) denote the transmission throughput from i to j at time t Let A(Υ) = Υ R(t)dt denote the data volume that can be 0 transmitted within a time period of Υ Provided Υ and content file size F ij to transmit, our goal is to 1. derive the expression of A(Υ) 2. evaluated the likelihood that A(Υ) > F ij 6

7 Analytical Framework At time t = 0, the evaluation is performed We perform the following 4 steps 0 Download subscription submitted at t = 0 7

8 Analytical Framework At time t = 0, the evaluation is performed We perform the following 4 steps 1 Estimate headway distance At time t 0 Download subscription submitted at t = 0 8

9 Analytical Framework At time t = 0, the evaluation is performed We perform the following 4 steps 2 Evaluate physical-layer capacity (function of distance) 1 Estimate headway distance At time t 0 Download subscription submitted at t = 0 9

10 Analytical Framework At time t = 0, the evaluation is performed We perform the following 4 steps 3 MAC throughput (function of physical-layer capacity) 2 Evaluate physical-layer capacity (function of distance) 1 Estimate headway distance At time t 0 Download subscription submitted at t = 0 10

11 Analytical Framework At time t = 0, the evaluation is performed We perform the following 4 steps 3 MAC throughput (function of physical-layer capacity) 4 Evaluate download volume as throughput integrated over time 2 Evaluate physical-layer capacity (function of distance) 1 Estimate headway distance At time t 0 Download subscription submitted at t = 0 11

12 Headway Distance Let H(t) denote the headway distance from i to j at time t H(t) 0 if i is ahead of j in the moving direction, otherwise, H(t) < 0 Let v i (resp. v j ) and a i (resp. a j ) denote the mean and variance, respectively, of the velocity of vehicle i (resp. j) We model H(t) as the queue length of a G/G/1 queue in the unit of meter We resort to the diffusion approximation to obtain the pdf of H(t) over time t 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 where µ = v j v i and σ = a j + a j H (t) = H (t + t) H (t) = µ t + Θ σ t,,,, G/G/1 12

13 Headway Distance (cont d) Let f H (x; r, t) denote the probability density function (pdf) of H (t) at time t, conditional on the initial queue length, and f H (x; r, t) = Pr{ x H (t) x + x H (0) = r}. where r denotes the initial headway distance, i.e., H(0) f H (x, r, t) can be characterized by the Kolmogorov equation (alternatively known as Fokker Planck equation) as 1 2 σ 2 x 2 f H (x; r, t) + µ x f H (x; r, t) = t f H (x; r, t) subject to the initial condition of the headway distance, According to [1], we have f H (x; r, t) = f H (x; r, 0) = δ (r), { } 1 (x r µt)2 exp 2πσt 2σt [1] D. R. Cox and H. D. Miller, The Theory of Stochastic Processes. Chapman & Hall/CRC,

14 Physical-layer Transmission Rate Let C(t) denote the physical-layer transmission rate from i to j C(t) is dependent on H(t) C(t) is subjected to the fast channel fadings from i and j We adopt the model in [2, 3] to derive the expression of C(t), which is represented by H(t) Ref. [2] characterizes the fast channel fading between two vehicles 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-Vehicle Narrow-band Channel Measurement and Characterization of the 5.9 GHz Dedicated Short Range Communication (DSRC) Frequency Band, IEEE Journal on Selected Areas in Communications, vol. 25, no. 8, pp , Oct [3] J. Yoo, B. S. C. Choi, and M. Gerla, An Opportunistic Relay Protocol for Vehicular Road-side Access with Fading Channels, in Proc. of IEEE ICNP,

15 MAC Throughput The MAC throughput represents the effective transmission rate from i to j with channel contentions taken into consideration We assume that the fundamental DCF MAC with RTS/CTS handshake is applied to schedule the channel access of nodes Let N denote the number of vehicles contending for the transmission with i N follows the Poisson distribution with known mean value Let τ denote the transmission probability of each vehicle and 1 τ = W/2 + 1 where W is the minimum contention window size The MAC throughput R is evaluated as R (t) =τp suc FL i T where P suc is the successful transmission probability. FL i is the frame length of i. T is the average length of a time slot (where C (t) comes into play) 15

16 Data Volume That Can Be Transmitted The data volume that can be transmitted within a time period Υ is thus A(Υ) = Υ 0 R(t)dt Evaluating A(Υ) with the above equation involves stochastic integral We evaluate its mean, E (A(Υ)), and the upper-bound of its variance, V(A(Υ)) instead Call Admission Control: with file size F ij known, the transmission request is admitted iff Pr { A(Υ) > F ij } > ξ Vehicle i (sender) File size Fij We apply the one-sided Chebyshev inequality to derive a sufficient condition on E (A(Υ)) and V(A(Υ)) to have above inequality satisfied, with Pr { } V (A) A F ij V (A) + [ ] 2 1 ξ E (A) F ij Vehicle j (receiver) 16

17 Simulation We evaluate the accuracy of the analysis and effectiveness of the call admission control scheme using a simulator coded in C++ We simulate 1000 vehicles on a highway section with mean inter-distance 60 meters The velocity of vehicles follows the normal distribution with the mean and standard deviation uniformly selected from [70, 130] km/h and [21, 39] km/h, respectively Channel fading between vehicles follows the Nakagami-m distribution with parameters derived in [2] 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 Channel Measurement and Characterization of the 5.9 GHz Dedicated Short Range Communication (DSRC) Frequency Band, IEEE Journal on Selected Areas in Communications, vol. 25, no. 8, pp , Oct

18 Accuracy of Analysis We focus on a randomly selected pair of vehicles and report the mean and variance of its data volume download over time Mean Data Volume (in bytes) x 107 Analysis Simulation Simulation Time (in seconds) Variance of Data Volume x Analysis Simulation Simulation Time (in seconds) The analysis of the mean data volume matches the simulations well As time increases, the gap between the upper bound of download volume variance and the simulation increases In real-world applications, connection time would be typically short 18

19 Effectiveness of Call Admission Control (CAC) Fraction of Fragment Contents std = 54 km/h, without CAC std = 30.6 km/h, without CAC std = 10.8 km/h, without CAC std = 54 km/h, with CAC std = 30.6 km/h, with CAC std = 10.8 km/h, with CAC Valid Data Volume (in bytes) 6 x std = 54 km/h, without CAC std = 30.6 km/h, without CAC std = 10.8 km/h, without CAC std = 54 km/h, with CAC std = 30.6 km/h, with CAC std = 10.8 km/h, with CAC 0 within [0,100s] within [0,450s] 0 within [0, 100s] within [0, 450s] With CAC applied, portion of fragment content transmissions reduces dramatically With CAC applied, the download volume of valid contents increases Small file size is favored 19

20 Conclusion The infotainment applications in VANET may boil down to the transmission of consecutive content files from send to receiver The contents need to be transmitted in their entirety so as to be useful to the on-top applications Existing literature largely focus on the packet-level performance in throughput and delay of packet transmissions, but neglect the session-level performance in terms of the integrity of content transmissions Given the mobility statistics of vehicles, we develop a mathematical framework to evaluate the data volume that can be transmitted among a random pair of vehicles Based on the model, we then propose a call admission control mechanism to filter to suspicious transmission requests Future work Extend the framework to multi-hop transmissions Develop the channel scheduling scheme to guarantee the integrity of content transmissions 20

21 Thank You! Slides are available at author s (Tom H. Luan) website: hluan Please forward your questions to the author through hluan@uwaterloo.ca 21