A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks

One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has attracted the researchers' consideration is congestion control. Accordingly, many algorithms have been proposed to alleviate the congestion problem, although it is hard to find an appropriate algorithm for applications and safety messages among them. Safety messages encompass beacons and event-driven messages. Delay and reliability are essential requirements for event-driven messages. In crowded networks where beacon messages are broadcasted at a high number of frequencies by many vehicles, the Control Channel (CCH), which used for beacons sending, will be easily congested. On the other hand, to guarantee the reliability and timely delivery of event-driven messages, having a congestion free control channel is a necessity. Thus, consideration of this study is given to find a solution for the congestion problem in VANETs by taking a comprehensive look at the existent congestion control algorithms. In addition, the taxonomy for congestion control algorithms in VANETs is presented based on three classes, namely, proactive, reactive and hybrid. Finally, we have found the criteria in which fulfill prerequisite of a good congestion control algorithm

Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

A Hybrid Model to Extend Vehicular Intercommunication V2V through D2D Architecture

In the recent years, many solutions for Vehicle to Vehicle (V2V) communication were proposed to overcome failure problems (also known as dead ends). This paper proposes a novel framework for V2V failure recovery using Device-to-Device (D2D) communications. Based on the unified Intelligent Transportation Systems (ITS) architecture, LTE-based D2D mechanisms can improve V2V dead ends failure recovery delays. This new paradigm of hybrid V2V-D2D communications overcomes the limitations of traditional V2V routing techniques. According to NS2 simulation results, the proposed hybrid model decreases the end to end delay (E2E) of messages delivery. A complete comparison of different D2D use cases (best & worst scenarios) is presented to show the enhancements brought by our solution compared to traditional V2V techniques.Comment: 6 page

The Study "Insightroads: Exploration of Data Dissemination Techniques for Ensuring Safety in Vanets"

Vehicle Ad Hoc Networks (VANETs) are ad hoc networks created for Intelligent Transportation Systems (ITS) in which vehicles communicate with one another to improve driving effectiveness and traffic safety without depending on a centralised infrastructure. To increase road safety, efficiency, and comfort, these networks allow vehicles to communicate data via sensors, GPS, and communication systems. By assuring accurate message transmission and lowering delivery delays, data dissemination mechanisms used in VANETs serve to further improve driver and passenger safety, productivity, and comfort. The existing literature on Vehicular Ad Hoc Networks (VANETs) includes a variety of proposed mechanisms for data dissemination. This paper aims to conduct literature review to examine the data dissemination techniques for safety applications in VANETs

A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Process

Scalability is one of the major issues for real-world Vehicle-to-Vehicle network realization. To tackle this challenge, a stochastic hybrid modeling framework based on a non-parametric Bayesian inference method, i.e., hierarchical Dirichlet process (HDP), is investigated in this paper. This framework is able to jointly model driver/vehicle behavior through forecasting the vehicle dynamical time-series. This modeling framework could be merged with the notion of model-based information networking, which is recently proposed in the vehicular literature, to overcome the scalability challenges in dense vehicular networks via broadcasting the behavioral models instead of raw information dissemination. This modeling approach has been applied on several scenarios from the realistic Safety Pilot Model Deployment (SPMD) driving data set and the results show a higher performance of this model in comparison with the zero-hold method as the baseline.Comment: This is the accepted version of the paper in 2018 IEEE 88th Vehicular Technology Conference (VTC2018-Fall) (references added, title and abstract modified