Challenges of Large-Challenges of Large-scale Vehicular & scale Vehicular & Mobile Ad hoc Network Mobile Ad hoc Network SimulationSimulation

Thomas D. Hewer, Maziar Nekovee, Thomas D. Hewer, Maziar Nekovee, Radhika S. Saksena and Peter V. CoveneyRadhika S. Saksena and Peter V. Coveneyt.hewer@cs.ucl.ac.ukt.hewer@cs.ucl.ac.uk maziar.nekovee@bt.commaziar.nekovee@bt.com

Centre for Computational Science, University College LondonCentre for Computational Science, University College London

and BT Researchand BT Research

Vehicular NetworkingVehicular Networking• Vehicular networks are formed when radio-Vehicular networks are formed when radio-

equipped vehicles come within range of one equipped vehicles come within range of one another or roadside equipmentanother or roadside equipment

• They can be used to disseminate traffic They can be used to disseminate traffic information, perform collision avoidance, information, perform collision avoidance, reduce congestion and improve the flow of reduce congestion and improve the flow of traffic through a systemtraffic through a system

• The latest telecommunications protocols and The latest telecommunications protocols and mechanisms are being implemented into cars mechanisms are being implemented into cars and equipment and must be tested and and equipment and must be tested and validatedvalidated

• Simulation allows for inexpensive research and Simulation allows for inexpensive research and developmentdevelopment

Network SimulationsNetwork Simulations

QuickTime™ and aMPEG-4 Video decompressor

are needed to see this picture.

QuickTime™ and aMPEG-4 Video decompressor

are needed to see this picture.

• Congestion reduction using inter-vehicular ad hoc communication to warn of an approaching obstacle

ProblemProblem• Current network simulation tools available Current network simulation tools available

require many CPU hours to run even small require many CPU hours to run even small simulations on a single-processor machinesimulations on a single-processor machine

• Given the applications required by vehicular Given the applications required by vehicular network simulations, the results are time-network simulations, the results are time-dependent and often urgentdependent and often urgent

• To this end a requirement exists to run complex To this end a requirement exists to run complex simulations more quickly than is achievable simulations more quickly than is achievable using off-the-shelf software and single-using off-the-shelf software and single-processorsprocessors

• HPC can enable this reduction in simulation HPC can enable this reduction in simulation runtime....runtime....

Vehicular ModellingVehicular Modelling

• Car following model (IDM from Treiber et al.(2000))

Calculate the gain from a lane change

MyAdv = anew − aold + bias

where a is the acceleration and bias applies road rules (i.e. drive in the right-hand lane where possible)

Calculate the disadvantage to users in the new lane if change occurs

OthDisAdv = abehind(old) − abehind(new)

the effects of this realistically model the risk assessment of changing lane

THRESHOLD?(MyAdv - p) * OthDisAdv >

• Lane-changing algorithm using acceleration gain method

Network SimulationsNetwork Simulations

• Nodes handling - movement and object parameters

• Packet handling - RAM considerations

• Models - complexity and variation

• Radiowave propagation - complexity vs. computation

cluster edge

message source

Nekovee and Bogason, 2007.

Field of Study - M25 Field of Study - M25 LondonLondon

• M25 London Orbital

• 121.5 miles long

• Longest ring road in the world

• 31 junctions

• 9 motorway interchanges

• Junction 15 to 14 carries 165000 cars per day

• Simulating just Junction 15 to 14 for 24 hours would take over a year to achieve on a single processor machine

Results - BenchmarkingResults - BenchmarkingThe CPU time taken to run a one hour simulation with flooding algorithm

Results - ExtrapolationResults - ExtrapolationExtrapolation of NS-2 simulation CPU consumption

ChallengesChallenges

• Packet Handling - system memory requirements increase exponentially as the number of messages sent/received/in transit increases

• Boundary Conditions - complex algorithms to allow seamless decomposition across different boundaries and high amounts of communication overhead

• HPC Infrastructure - network, disk, file I/O considerations

• Global Knowledge Requirements - radiowave propagation and pathloss models require long-distance calculations over the number of nodes to accurately measure SNR, reception probability etc.

Decomposition Decomposition TechniquesTechniques• Domain and task farming algorithms for vehicular simulations require

much boundary communication, at every timestep of the simulation (a million events per second)

• Component decomposition allows us to keep this boundary communication low but still keep the simulation free of causality/synchronisation problems

• The processors can operate asynchronously for events that occur only in their own scope, and can perform mass-transit data shifts at greater time intervals

• Technique: split the nodes into lists (per processor available), create a global simulation object on each processor and perform all processing for each node on it’s home processor, then update the global object

• How we split the nodes into the component lists heavily influences the efficiency of the simulation performance, so node clusters should be assigned to the same processor where possible

• Hierarchical binning methods can be useful here, especially where nodes are constrained to roadways

Parameter SearchParameter Search• One useful method of simulation for vehicular networks is to search

through all the various parameters of the models involved

• With so many parameters and scenarios the ability to run each parameter ‘set’ on an individual processor is highly desirable

• Processors may operate completely independently and still share a central dataset, leading to much more efficient use of processing power

• The stochastic analysis of different settings in a simulation is useful for decision-making systems

• It also allows us to test new theories regarding power, coding techniques etc.

Looking ForwardLooking Forward

• Multi-resolution simulationsMulti-resolution simulations

• VisualisationVisualisation

• Steering Steering

• Intelligent Transport SystemsIntelligent Transport Systems

• Collision AvoidanceCollision Avoidance

• Emission Monitoring/ReductionEmission Monitoring/Reduction

ThankyouThankyou