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VANET:On mobility Scenarios and Urban Infrastructure. & Realistic Simulation of Network Protocols in VANET Scenarios. Advisor: Kai-Wei Ke Speaker: Chia-Ho Chao Date: 22/04/2008. VANET:On mobility Scenarios and Urban Infrastructure. Outline. Overview of TRANSIMS Overview of CORSIM
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VANET:On mobility Scenarios and Urban Infrastructure.&Realistic Simulation of Network Protocols in VANET Scenarios Advisor: Kai-Wei Ke Speaker: Chia-Ho Chao Date: 22/04/2008
Outline • Overview of TRANSIMS • Overview of CORSIM • Random waypoint (RWP) • Mobility Models Comparison • Flat Network • Opportunistic Infrastructure • Inter-contact Times • Afternoon Trend • Conclusion
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.
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
Simulation setting • VANET simulations are run for 200 seconds on a 1*2 km rectangle on the map. • Highest AP density
Using TRANSIMS mobility traces 7am no APs 8am no APs
Using RWP model 7am no APs 8am no APs
Using CORSIM mobility traces 7am no APs 8am no APs
Using TRANSIMS mobility traces 7am with APs 8am with APs
Using RWP model 7am with APs 8am with APs
Using CORSIM mobility traces 7am with APs 8am with APs
Mobility Models Comparison:Inter-contact TimesandAfternoon trend
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.
Realistic Simulation of Network Protocols in VANET Scenarios
Outline • Traffic Simulation • Network Simulation • Coupling Traffic Microsimulation and Network Simulation • Simulation Result • Conclusion
Traffic Simulation • Macroscopic models • METACOR • Mesoscopic models • CONTRAM • Microscopic models • Cellular Automaton model (CA) • SK model • IDM/MOBIL model
Intelligent-Driver Model(IDM) • Car-following model Desired gap Minimum gap(jam) Additional gap(driving) Time headway Difference in speed a:comfortable acceleration b:comfortable deceleration Acceleration exponent acceleration Desired velocity The gap to a vehicle in front
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 Desired gap Maximum safe deceleration Bias to the right lane
OMNeT++ • A discrete event simulation environment. • primary application area is the simulation of communication networks • GUI support • INET Framework
DYMO Routing Protocol • DYMO: Dynamic MANET On-Demand • Reactive A AB A ABC A A B C D AODV DYMO DCB D DC D D
DYMO and support modules in the protocol stack App1 App2 DYMO Transport Layer queue hook Network Layer Data Link Layer
Coupling Traffic Microsimulation and Network Simulation Excerpt from the traffic simulation’s output stream
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.
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/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.
