VANET:On mobility Scenarios and Urban Infrastructure.

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VANETOn mobility Scenarios and Urban
Infrastructure.Realistic Simulation of Network
Protocols in VANET Scenarios

• Advisor Kai-Wei Ke
• Speaker Chia-Ho Chao
• Date 22/04/2008

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VANETOn mobility Scenarios and Urban
Infrastructure.
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Outline

• Overview of TRANSIMS
• Overview of CORSIM
• Random waypoint (RWP)
• Mobility Models Comparison
• Flat Network
• Opportunistic Infrastructure
• Inter-contact Times
• Afternoon Trend
• Conclusion

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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 CPU
• Lack of activity flow information

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RWP
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Mobility Models ComparisonSimulation setting
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Simulation setting

• VANET simulations are run for 200 seconds on a
  12 km rectangle on the map.
• Highest AP density

7AM 8AM
Average vehicles 270 371
Average speed per second 12.6 m/s 12.5 m/s
Stop time(seconds) 3.2 5.7
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Mobility Models ComparisonFLAT NETWORK
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Using TRANSIMS mobility traces
7am no APs
8am no APs
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Using RWP model
7am no APs
8am no APs
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Using CORSIM mobility traces
7am no APs
8am no APs
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Mobility Models ComparisonOPPORTUNISTIC
INFRASTRUCTURE
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Simulation Setting
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Simulation Setting
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Using TRANSIMS mobility traces
7am with APs
8am with APs
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Using RWP model
7am with APs
8am with APs
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Using CORSIM mobility traces
7am with APs
8am with APs
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Mobility Models ComparisonInter-contact
TimesandAfternoon 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 Simulation
• Network Simulation
• Coupling Traffic Microsimulation and Network
  Simulation
• Simulation Result
• Conclusion

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Traffic Simulation

• Macroscopic models
• METACOR
• Mesoscopic models
• CONTRAM
• Microscopic models
• Cellular Automaton model (CA)
• SK model
• IDM/MOBIL model

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Intelligent-Driver Model(IDM)

• Car-following model

Difference in speed
Time headway
Additional gap(driving)
Minimum gap(jam)
Desired gap
acomfortable acceleration bcomfortable
deceleration
Acceleration exponent
acceleration
The gap to a vehicle in front
Desired velocity
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MOBIL

• MOBIL
• Minimizing Overall Braking decelerations
  Induced by Lane change
• Have to be fulfilled two criteria
• The lane change has to be safe.

politeness factor
Lane change threshold
Desired gap
b)
Acceleration
Maximum safe deceleration
Desired gap
Bias to the right lane
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Road Traffic Microsimulation Parameters
Car Track
Desired velocity V0 33.0m/s 22.2 m/s
Time headway T 1.5s 1.7s
Comfortable acceleration a 0.73m/s2 0.73 m/s2
Comfortable deceleration b 1.67m/s2 1.67 m/s2
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/s2 4 m/s2
Lane change threshold athr 0.3 m/s2 0.2 m/s2
Bias to the right lane ?b 0.1 rm/s2 0.3 m/s2
d
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OMNeT

• A discrete event simulation environment.
• primary application area is the simulation of
  communication networks
• GUI support
• INET Framework

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DYMO Routing Protocol

• DYMO Dynamic MANET On-Demand
• Reactive

A
A
A
AB
ABC
A
B
C
D
AODV
DYMO
DCB
D
D
D
DC
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DYMO and support modules in the protocol stack
App1
App2
DYMO
TCP.mss 1024Byte
TCP.advertisedWindow 14336Byte
TCP.tcpAlgorithmClass TCPReno
Transport Layer
queue
hook
Network Layer
ARP.retryTimeout 1s
ARP.retryCount 3
ARP.cacheTimeout 100s
mac.address auto
mac.bitrate 11Mbit/s
mac.broadcastBackoff 31slots
mac.QueueSize 14Pckts
mac.rtsCts False
Data Link Layer
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Simulated VANET Scenario

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Coupling Traffic Microsimulation and Network
Simulation
Car icar0_ Car icar1_ Car Icar1_
3187,1487 3187,1490 3187,1493 3187,1495 3187,1498 3187,1501 3188,1504 3171,1380 3172,1387 3173,1394 3174,1402 3175,1409 3176,1417 3177,1425 3154,1262 3156,1269 3153,1277 3155,1284 3156,1291 3158,1299 3159,1306
Excerpt from the traffic simulations output
stream
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Simulation Result
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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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Reference

• G. 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/c
  orsim.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!