Vehicular ad hoc networks (Computer networks)--Technological innovations.

This work presents the implementations of three adaptive broadcast protocols for vehicular ad hoc networks (VANET) using the Network Simulator 3 (Ns-3). Performing real life tests for VANET protocols is very costly and risky, so simulation becomes a viable alternative technique. Ns-3 is one of the most advanced open source network simulators. Yet Ns-3 lacks implementations of broadcast protocols for VANET. We first implement the Distance to Mean (DTM) protocol, which uses the distance to mean to determine if a node should rebroadcast or not. We then implement the Distribution-Adaptive Distance with Channel Quality (DADCQ) protocol, which uses node distribution, channel quality and distance to determine if a node should favor rebroadcasting. The third protocol, Statistical Location-Assisted Broadcast protocol (SLAB), is an improvement of DADCQ which automates the threshold function design using machine learning. Our NS-3 implementations of the three protocols have been validated against their JiST/SWANS implementations.

Vehicular Ad hoc NETworks (VANETs) are a subclass of Mobile Ad hoc NETworks
and represent a relatively new and very active field of research. VANETs will enable in
the near future applications that will dramatically improve roadway safety and traffic
efficiency. There is a need to increase traffic efficiency as the gap between the traveled
and the physical lane miles keeps increasing. The Dynamic Traffic Assignment problem
tries to dynamically distribute vehicles efficiently on the road network and in accordance
with their origins and destinations. We present a novel dynamic decentralized and
infrastructure-less algorithm to alleviate traffic congestions on road networks and to fill
the void left by current algorithms which are either static, centralized, or require
infrastructure. The algorithm follows an online approach that seeks stochastic user
equilibrium and assigns traffic as it evolves in real time, without prior knowledge of the traffic demand or the schedule of the cars that will enter the road network in the future.
The Reverse Online Algorithm for the Dynamic Traffic Assignment inspired by Ant
Colony Optimization for VANETs follows a metaheuristic approach that uses reports from
other vehicles to update the vehicle’s perceived view of the road network and change route
if necessary. To alleviate the broadcast storm spontaneous clusters are created around
traffic incidents and a threshold system based on the level of congestion is used to limit
the number of incidents to be reported. Simulation results for the algorithm show a great
improvement on travel time over routing based on shortest distance. As the VANET
transceivers have a limited range, that would limit messages to reach at most 1,000 meters,
we present a modified version of this algorithm that uses a rebroadcasting scheme. This
rebroadcasting scheme has been successfully tested on roadways with segments of up to
4,000 meters. This is accomplished for the case of traffic flowing in a single direction on
the roads. It is anticipated that future simulations will show further improvement when
traffic in the other direction is introduced and vehicles travelling in that direction are
allowed to use a store carry and forward mechanism.