VANET:On mobility Scenarios and Urban Infrastructure. & Realistic Simulation of Network Protocols in VANET Scenarios Advisor: Kai-Wei Ke Speaker: Chia-Ho Chao Date: 22/04/ /4/221

VANET:On mobility Scenarios and Urban Infrastructure. 2008/4/222

Outline Overview of TRANSIMS Overview of CORSIM Random waypoint (RWP) Mobility Models Comparison Flat Network Opportunistic Infrastructure Inter-contact Times Afternoon Trend Conclusion 2008/4/223

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. 2008/4/224

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 2008/4/225

RWP 2008/4/226

Mobility Models Comparison: Simulation setting 2008/4/227

Simulation setting VANET simulations are run for 200 seconds on a 1*2 km rectangle on the map. Highest AP density 7AM8AM Average vehicles Average speed per second 12.6 m/s 12.5 m/s Stop time(seconds)3.25.7

Mobility Models Comparison: FLAT NETWORK 2008/4/229

Using TRANSIMS mobility traces 2008/4/2210 8am no APs 7am no APs

Using RWP model 2008/4/2211 8am no APs 7am no APs

Using CORSIM mobility traces 2008/4/2212 8am no APs 7am no APs

Mobility Models Comparison: OPPORTUNISTIC INFRASTRUCTURE 2008/4/2213

Simulation Setting 2008/4/2214

Simulation Setting 2008/4/2215

Using TRANSIMS mobility traces 2008/4/2216 8am with APs 7am with APs

Using RWP model 2008/4/2217 8am with APs 7am with APs

Using CORSIM mobility traces 2008/4/2218 8am with APs 7am with APs

Mobility Models Comparison: Inter-contact Times and Afternoon trend 2008/4/2219

TRANSIMS mobility traces at 7AM 2008/4/2220

TRANSIMS mobility traces at 8AM 2008/4/2221

Afternoon trend 2008/4/2222

Afternoon trend 2008/4/2223

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. 2008/4/2224

Realistic Simulation of Network Protocols in VANET Scenarios 2008/4/2225

Outline Traffic Simulation Network Simulation Coupling Traffic Microsimulation and Network Simulation Simulation Result Conclusion 2008/4/2226

Traffic Simulation Macroscopic models METACOR Mesoscopic models CONTRAM Microscopic models Cellular Automaton model (CA) SK model IDM/MOBIL model 2008/4/2227

Intelligent-Driver Model(IDM) Car-following model 2008/4/2228 The gap to a vehicle in front Difference in speed Desired velocity Time headway a:comfortable acceleration b:comfortable deceleration Acceleratio n exponent Additional gap(driving) Minimum gap(jam) Desired gap acceleration

MOBIL MOBIL: Minimizing Overall Braking decelerations Induced by Lane change Have to be fulfilled two criteria: a)The lane change has to be safe. 2008/4/2229 Maximum safe deceleration Desired gap Acceleration b) Bias to the right lane politeness factor Lane change threshold

Road Traffic Microsimulation Parameters CarTrack Desired velocityV0V0 33.0m/s22.2 m/s Time headwayT1.5s1.7s Comfortable accelerationa0.73m/s^2 Comfortable decelerationb1.67m/s^2 Acceleration exponent44 Minimum gap (jam) S 0 2m Additional gap (driving) S 1 0m Vehicle length l6m10m Politeness factor P20% Maximum safe decelerationb save 4m/s^2 Lane change thresholda thr 0.3 m/s^20.2 m/s^2 Bias to the right lane △b△b 0.1 rm/s^20.3 m/s^2 2008/4/2230 δ

OMNeT++ A discrete event simulation environment. primary application area is the simulation of communication networks GUI support INET Framework 2008/4/2231

DYMO Routing Protocol DYMO: Dynamic MANET On-Demand Reactive 2008/4/2232 ABCD AODV AAA DDD DYMO ABABC DC DCB

DYMO and support modules in the protocol stack 2008/4/2233 App1 App2 DYMO Transport Layer Network Layer Data Link Layer queue hook TCP.mss1024Byte TCP.advertisedWindow14336Byte TCP.tcpAlgorithmClassTCPReno ARP.retryTimeout1s ARP.retryCount3 ARP.cacheTimeout100s mac.addressauto mac.bitrate11Mbit/s mac.broadcastBackoff31slots mac.QueueSize14Pckts mac.rtsCtsFalse

Simulated VANET Scenario 2008/4/2234

Coupling Traffic Microsimulation and Network Simulation 2008/4/2235 Car ; i=car0_[…]Car ; i=car1_[…]Car ; I=car1_[…] 3187, , , , , , ,1504 […] 3171, , , , , , ,1425 […] 3154, , , , , , ,1306 […] Excerpt from the traffic simulation’s output stream

Simulation Result 2008/4/ %

Simulation Result 2008/4/2237

Simulation Result 2008/4/2238

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. 2008/4/2239

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,” m.htmhttp://mctrans.ce.ufl.edu/featured/TSIS/Version5/corsi m.htm. I. Dietrich, C. Sommer, and F. Dressler, "Simulating DYMO in OMNeT++," University of Erlangen, Dept. of Computer Science 7, Technical Report 01/07, April /4/2240

2008/4/2241 Thanks for your attention!