VANET:On mobility Scenarios and Urban Infrastructure.

&Realistic Simulation of Network Protocols in VANET Scenarios

Advisor: Kai-Wei KeSpeaker: Chia-Ho Chao

Date: 22/04/2008

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VANET:On mobility Scenarios and Urban Infrastructure.

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Outline

Overview of TRANSIMS Overview of CORSIMRandom waypoint (RWP)Mobility Models Comparison

Flat NetworkOpportunistic InfrastructureInter-contact TimesAfternoon Trend

Conclusion2008/4/22 3

TRANSIMS Traces

TRANSIMS : Transportation Analysis Simulation System

Asses the performance of a large scale urban sensor network.Creating car movement patterns based on activity flows by large scale, vehicular traffic and parallel simulator.

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CORSIM Traces

CORSIM : Microscopic Traffic Simulation Model

high level of precision in vehicular traffic simulation.difference from TRANSIMS:

Single CPULack of activity flow information

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RWP

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Mobility Models Comparison:Simulation setting

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Simulation setting

VANET simulations are run for 200 seconds on a 1*2 km rectangle on the map.Highest AP density 7AM 8AM

Average vehicles 270 371

Average speed per second

12.6m/s

12.5m/s

Stop time(seconds) 3.2 5.7

Mobility Models Comparison:FLAT NETWORK

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Using TRANSIMS mobility traces

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8am no APs

7am noAPs

Using RWP model

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8am no APs

7am noAPs

Using CORSIM mobility traces

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8am no APs

7am noAPs

Mobility Models Comparison:OPPORTUNISTIC

INFRASTRUCTURE

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Simulation Setting

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Simulation Setting

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Using TRANSIMS mobility traces

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8am with APs

7am withAPs

Using RWP model

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8am with APs

7am withAPs

Using CORSIM mobility traces

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8am with APs

7am withAPs

Mobility Models Comparison:Inter-contact Times

andAfternoon trend

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TRANSIMS mobility traces at 7AM

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TRANSIMS mobility traces at 8AM

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Afternoon trend

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Afternoon trend

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Conclusion

The results confirm that open APs can be effectively exploited to dramatically improve performance.A correct model of traffic flows is important.In long timeframes during the day (i.e. rush hours), network becomes static.

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Realistic Simulation of Network Protocols in VANET Scenarios

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Outline

Traffic SimulationNetwork SimulationCoupling Traffic Microsimulation and Network SimulationSimulation ResultConclusion

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Traffic Simulation

Macroscopic modelsMETACOR

Mesoscopic modelsCONTRAM

Microscopic modelsCellular Automaton model (CA)SK modelIDM/MOBIL model

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Intelligent-Driver Model(IDM)

Car-following model

2008/4/22 28The gap to a

vehicle in front

Difference in speed

Desired velocity

Time headway

a:comfortable accelerationb:comfortable deceleration

Acceleration exponent

Additional gap(driving)

Minimum gap(jam)

Desired gap

acceleration

MOBIL

MOBIL: Minimizing Overall Braking decelerations

Induced by Lane changeHave to be fulfilled two criteria:a) The lane change has to be safe.

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Maximum safe

deceleration

Desired gap

Desired gap

Accelerationb)

Bias to the right

lane

politeness factor

Lane change

threshold

Road Traffic Microsimulation ParametersCar Track

Desired velocity V0 33.0m/s 22.2 m/s

Time headway T 1.5s 1.7s

Comfortable acceleration a 0.73m/s^2 0.73 m/s^2

Comfortable deceleration b 1.67m/s^2 1.67 m/s^2

Acceleration exponent 4 4

Minimum gap (jam) S0 2m 2m

Additional gap (driving) S1 0m 0m

Vehicle length l 6m 10m

Politeness factor P 20% 20%

Maximum safe deceleration bsave 4m/s^2 4 m/s^2

Lane change threshold athr 0.3 m/s^2 0.2 m/s^2

Bias to the right lane △ b 0.1 rm/s^2 0.3 m/s^2

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δ

OMNeT++

A discrete event simulation environment.primary application area is the simulation of communication networksGUI supportINET Framework

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DYMO Routing Protocol

DYMO: Dynamic MANET On-Demand Reactive

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A B C DAODV

A A A

D D D

DYMO

AB ABC

DCDCB

DYMO and support modules in the protocol stack

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App1 App2 DYMO

Transport Layer

Network Layer

Data Link Layer

queue

hook

TCP.mss 1024Byte

TCP.advertisedWindow 14336Byte

TCP.tcpAlgorithmClass TCPReno

ARP.retryTimeout 1s

ARP.retryCount 3

ARP.cacheTimeout 100smac.address auto

mac.bitrate 11Mbit/s

mac.broadcastBackoff 31slots

mac.QueueSize 14Pckts

mac.rtsCts False

Simulated VANET Scenario

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Coupling Traffic Microsimulation and Network Simulation

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Car ; i=car0_[…] Car ; i=car1_[…] Car ; I=car1_[…]

3187,14873187,14903187,14933187,14953187,14983187,15013188,1504

[…]

3171,13803172,13873173,13943174,14023175,14093176,14173177,1425

[…]

3154,12623156,12693153,12773155,12843156,12913158,12993159,1306

[…]

Excerpt from the traffic simulation’s output stream

Simulation Result

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15%

Simulation Result

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Simulation Result

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Conclusion

Integrated the traffic model in network simulation in order to improve the quality of network simulations. Simulation setups using simple mobility models often produce skewed results compared to the application of traffic models.

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ReferenceG. Marfia, G. Pau, E. De Sena, E. Giordano, M. Gerla, “Evaluating Vehicle Network Strategies for Downtown Portland: opportunistic infrastructure and the importance of realistic mobility models,”http://transims.tsasa.lanl.gov/.http://mctrans.ce.ufl.edu/featured/TSIS/Version5/corsim.htm.http://www.omnetpp.org/I. Dietrich, C. Sommer, and F. Dressler, "Simulating DYMO in OMNeT++," University of Erlangen, Dept. of Computer Science 7, Technical Report 01/07, April 2007.

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Thanks for your attention!