Jérôme Härri, Fethi Filali, Christian Bonnet {haerri ,filali,bonnet } @eurecom.fr

On Meaningful Parameters for Routing in VANETs Urban Environments under Realistic Mobility Patterns Jérôme Härri, Fethi Filali, Christian Bonnet {haerri,filali,bonnet}@eurecom.fr Institut Eurécom Mobile Communications Department Sophia Antipolis, France Eurécom Seminar Series Sophia-Antipolis January 18st 2007

Agenda • Motivation • VanetMobiSim: Realistic Mobility Simulator • Incidence on Vehicular Mobility Patterns • New Parameters for Performance evaluation • Incidence on the Performance of Routing Protocols • Conclusion et Future Work

Motivation • VANETs in urban areas have special characteristics that make standard wireless protocols inefficient or unusable • higher speed • non-uniform distribution of vehicles and speed • short transmission range • non random mobility patterns • Many academic researches carried on routing protocols have been done using random mobility models and uniform distribution of speed and vehicles. • Routing Performance is greatly dependent to the availability and the stability of wireless links • Closely tied to the mobility model • Can we assume that the performance of routing protocols will be identical to that under random mobility patterns ? • Can we actualy use the same performance evaluation parameters ?

VanetMobiSim • Written in JAVA • Platform independent • Configured by XML files • Produces traces for different network simulators (ns-2, QualNet..) • Simulator independent • Compatibility with a ns-2module for realistic radio propagation model in presence of buildings1 • Graphically displays vehicles mobility • Publicly available at : http://vanet.eurecom.fr [1] Stepanov et al., Universitat Stuttgart, CANU project

Features • Macroscopic Features: • Random or Imported Topological Maps (TIGER, GDF) • Stops and Traffic lights-based Intersections • Bi-directional roads • Single lane and multi-lanes roads • Microscopic Features: • Car-to-car interaction • Acceleration, deceleration based on the Intelligent Driver Model (IDM) • Intelligent Driver Model with Lane Changing (IDM-LC) based on the MOBIL model • Car-to-road infrastructure interaction • Interactions with traffic and stop signs based on the Intersection management (IDM-IM) [1] Treiber, Helbing, Universitat Dresden, Physical Review Aug 2000 [2] Treiber, Helbing, Universitat Dresden, ASIM 2002

Non Uniform Position Distribution Vehicular distribution on an urban topology with RWM

Non Uniform Position Distribution Vehicular distribution on an urban topology with VMM

Non Uniform Speed Distribution Vehicular speed distribution on an urban topology with VMM

Speed Decay Speed decay as a function of the average velocity Speed decay as a function of the density of vehicles

Realistic Mobility Models for Vanets • Are the vehicles’ positions uniformly distributed ? NO ! • Is the speed uniformly distributed ? NO ! • Do we actually get the speed we configured ? Again NO ! • Are we even in control here ?

New Parameters for Performance evaluation • What is really controlling the mobility patterns ? • Nodes average density ? Not Really ! • Nodes average velocity ? Not Really ! • So, what else ? • Road Segment length • Acceleration • Cluster Effect

Speed Decay Speed decay as a function of the length of the road segments Speed decay as a function of the acceleration

True Vehicular Speed on a Single Trip Average length of the road segments: 100m Average length of the road segments: 250m

Scenarios Characteristics Micro-model Parameters Simulation Parameters Macro-model Parameters

Scenarios Characteristics Simulation Scenarios Simulation Environment

Performance Evaluation Packet Delivery Ratio (PDR) as a function of the average velocity

Performance Evaluation Route hop-length as a function of the average velocity

Performance Evaluation End-to-end delay as a function of the average velocity

Performance Evaluation Packet Delivery Ration as a function of the length of the road segments

Performance Evaluation Route hop-length as a function of the length of the road elements

Performance Evaluation Packet Delivery Ratio as a function of the cluster effect

Performance Evaluation Route hop-length as a function of the cluster effect

Performance Evaluation End-to-end delay as a function of the cluster effect

Conclusion • We illustrated how a realistic mobility model for VANETs impacts vehicular mobility patterns • We evaluated the performance of AODV under realistic mobility patterns. • Some parameters have no influence in VANET with realistic mobility patterns. • New parameters has been proposed that have a more significant influence • We compared those results with non realistic random motion patterns. • Realistic mobility patterns has major influence on the performance • all performance metrics are improved • network connectivity is not fair • Good connectivity in clusters • Connectivity between clusters depends on the inter-distance between clusters • shorter route length • But longer hop length

Conclusion • We illustrated some effects of realistic mobility patterns on evaluation parameters • Velocity is not a good performance evaluation metric • We should better choose • Road segment length • Acceleration • Cluster effect • Intersection distribution • Intersection policy Future Work • Radio Obstacles • New universal metric that controls the large configuration parameters of VanetMobiSim.

Questions ? Jérôme Härri haerri@eurecom.fr

Jérôme Härri, Fethi Filali, Christian Bonnet {haerri ,filali,bonnet } @eurecom.fr