Beaconing Approaches in Vehicular Ad Hoc Networks: A Survey

A Vehicular Ad hoc Network (VANET) is a type of wireless ad hoc network that facilitates ubiquitous connectivity between vehicles in the absence of fixed infrastructure. Beaconing approaches is an important research challenge in high mobility vehicular networks with enabling safety applications. In this article, we perform a survey and a comparative study of state-of-the-art adaptive beaconing approaches in VANET, that explores the main advantages and drawbacks behind their design. The survey part of the paper presents a review of existing adaptive beaconing approaches such as adaptive beacon transmission power, beacon rate adaptation, contention window size adjustment and Hybrid adaptation beaconing techniques. The comparative study of the paper compares the representatives of adaptive beaconing approaches in terms of their objective of study, summary of their study, the utilized simulator and the type of vehicular scenario. 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Supporting Protocols for Structuring and Intelligent Information Dissemination in Vehicular Ad Hoc Networks

The goal of this dissertation is the presentation of supporting protocols for structuring and intelligent data dissemination in vehicular ad hoc networks (VANETs). The protocols are intended to first introduce a structure in VANETs, and thus promote the spatial reuse of network resources. Segmenting a flat VANET in multiple cluster structures allows for more efficient use of the available bandwidth, which can effectively increase the capacity of the network. The cluster structures can also improve the scalability of the underlying communication protocols. The structuring and maintenance of the network introduces additional overhead. The aim is to provide a mechanism for creating stable cluster structures in VANETs, and to minimize this associated overhead. Further a hybrid overlay-based geocast protocol for VANETs is presented. The protocol utilizes a backbone overlay virtual infrastructure on top of the physical network to provide geocast support, which is crucial for intervehicle communications since many applications provide group-oriented and location-oriented services. The final contribution is a structureless information dissemination scheme which creates a layered view of road conditions with a diminishing resolution as the viewing distance increases. Namely, the scheme first provides a high-detail local view of a given vehicle\u27s neighbors and its immediate neighbors, which is further extended when information dissemination is employed. Each vehicle gets aggregated information for road conditions beyond this extended local view. The scheme allows for the preservation of unique reports within aggregated frames, such that safety critical notifications are kept in high detail, all for the benefit of the driver\u27s improved decision making during emergency scenarios

Routing Protocols in Vehicular Ad hoc Networks: Survey and Research Challenges

A Vehicular Ad hoc Network (VANET) is a type of wireless ad hoc network that facilitates ubiquitous connectivity between vehicles in the absence of fixed infrastructure. Mul ti-hop routing and beaconing approaches are two important research challenges in high mobility vehicular networks. Routing protocols are divided into two categories of topology-based and position-based routing protocols. In this article, we perform a comparative study among the existing routing solutions, which explores the main advantages and drawbacks behind their design. After implementing the representatives of geographical and topology routing protocols, we analyze the simulation results and discuss the strengths and weaknesses of these routing protocols with regard to their suitability to vehicular networks. Lastly, we discuss the open issues and research directions related to VANET routing protocols.Ghafoor, KZ.; Mohammed, M.; Lloret, J.; Abu Bakar, K.; Zainuddin, ZM. (2013). Routing Protocols in Vehicular Ad hoc Networks: Survey and Research Challenges. Network Protocols and Algorithms. 5(4):39-83. doi:10.5296/npa.v5i4.4134S39835

Deep Kalman neuro fuzzy-based adaptive broadcasting scheme for Vehicular Ad Hoc Network: A context-aware approach

Vehicular Ad Hoc Networks (VANETs) are among the main enablers for future Intelligent Transportation Systems (ITSs) as they facilitate information sharing, which improves road safety, traffic efficiency, and provides passengers' comfort. Due to the dynamic nature of VANETs, vehicles need to exchange the Cooperative Awareness Messages (CAMs) more frequently to maintain network agility and preserve applications' performance. However, in many situations, broadcasting at a high rate leads to congest the communication channel, rendering VANET unreliable. Existing broadcasting schemes designed for VANET use partial context variables to control the broadcasting rate. Additionally, CAMs uncertainty, which is context-dependent has been neglected and a predefined fixed certainty threshold has been used instead, which is not suitable for the highly dynamic context. Consequently, vehicles disseminate a high rate of unnecessary CAMs which degrades VANET performance. A good broadcasting scheme should accurately determine which and when CAMs are broadcasted. To this end, this study proposes a Context-Aware Adaptive Cooperative Awareness Messages Broadcasting Scheme (CA-ABS) using combinations of Adaptive Kalman Filter, Autoregression, and Sequential Deep Learning and Fuzzy inference system. Four context variables have been used to represent the vehicular context, namely, individual driving behaviors, CAMs uncertainty, vehicle density, and traffic flow. Kalman Filter and Autoregression are used to estimate and predict the CAMs messages respectively. The deep learning model has been constructed to estimate the CAMs' uncertainties which is an important context variable that has been neglected in the previous research. Fuzzy Inference System takes context variables as input and determines an accurate broadcasting threshold and broadcasting interval. Extensive simulations have been conducted to evaluate the proposed scheme. Results show that the proposed scheme improves the CAMs delivery ratio and decreases the CAMs prediction errors

Dynamic speed adaptive classified (D-SAC) data dissemination protocol for improving autonomous robot performance in VANETs

In robotics, mechanized and computer simulation for accurate and fast crash detection between general geometric models is a fundamental problem. The explanation of this problem will gravely improve driver safety and traffic efficiency, vehicular ad hoc networks (VANETs) have been employed in many scenarios to provide road safety and for convenient travel of the people. They offer self-organizing decentralized environments to disseminate traffic data, vehicle information and hazardous events. In order to avoid accidents during roadway travels, which are a major burden to the society, the data, such as traffic data, vehicle data and the road condition, play a critical role. VANET is employed for disseminating the data. Still the scalability issues occur when the communication happens under high-traffic regime where the vehicle density is high. The data redundancy and packet collisions may be high which cause broadcast storm problems. Here the traffic regime in the current state is obtained from the speed of the vehicle. Thus the data reduction is obtained. In order to suppress the redundant broadcast D-SAC data, dissemination protocol is presented in this paper. Here the data are classified according to its criticality and the probability is determined. The performance of the D-SAC protocol is verified through conventional methods with simulation

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

A Kinetic Distance-to-Mean Based Routing Algorithm for Vehicular Ad-Hoc Networks

Vehicular Ad-hoc Network (VANET) allows vehicles to send information to each other or to roadside equipment in an instant and a wireless manner. It represents a considerable step forward in terms of transportation. Indeed, many applications could benefit from instantly transmitting data such as video and music streaming. Internet connectivity could also be available to the passengers. The main objective and improvement aimed by VANET is a security matter. Warning messages for weather conditions, traffic accidents and fuel consumption instantly transmitted between vehicles would improve road safety. However, one of the critical issues in VANET is the dissemination of messages throughout the network. Indeed, routing algorithms are a key issue because of the high mobility and scalability of VANET compared to other ad-hoc networks. This thesis contributes to the research area by firstly presenting a survey over most of the routing protocol used in VANET and classifying them according to the algorithm used. Secondly, this thesis develops more on the broadcasting algorithm category and particularly on the distance to mean heuristic method that presents good results in terms of reachability and bandwidth consumption. However, distance to mean protocol needs periodic beacons that creates a consequent overhead compared to instant rebroadcasting algorithm. Therefore, this thesis improves this method by reducing overhead using a bio inspired kinetic graph model proposed in the literature. The proposed modified algorithm has been implemented, simulated and evaluated in the network simulator NS3. Results show a lower overhead while preserving a good reachability

Video Streaming over Vehicular Ad Hoc Networks: A Comparative Study and Future Perspectives

Vehicular  Ad Hoc Network  (VANET) is emerged as an important research area that provides ubiquitous short-range connectivity among moving vehicles.  This network enables efficient traffic safety and infotainment applications. One of the promising applications is video transmission in vehicle-to-vehicle or vehicle-to-infrastructure environments.  But, video streaming over vehicular environment is a daunting task due to high movement of vehicles. This paper presents a survey on state-of-arts of video streaming over VANET. Furthermore, taxonomy of vehicular video transmission is highlighted in this paper with special focus on significant applications and their requirements with challenges, video content sharing, multi-source video streaming and video broadcast services. The comparative study of the paper compares the video streaming schemes based on type of error resilient technique, objective of study, summary of their study, the utilized simulator and the type of video sharing.  Lastly, we discussed the open issues and research directions related to video communication over VANET

SCALABLE MULTI-HOP DATA DISSEMINATION IN VEHICULAR AD HOC NETWORKS

Vehicular Ad hoc Networks (VANETs) aim at improving road safety and travel comfort, by providing self-organizing environments to disseminate traffic data, without requiring fixed infrastructure or centralized administration. Since traffic data is of public interest and usually benefit a group of users rather than a specific individual, it is more appropriate to rely on broadcasting for data dissemination in VANETs. However, broadcasting under dense networks suffers from high percentage of data redundancy that wastes the limited radio channel bandwidth. Moreover, packet collisions may lead to the broadcast storm problem when large number of vehicles in the same vicinity rebroadcast nearly simultaneously. The broadcast storm problem is still challenging in the context of VANET, due to the rapid changes in the network topology, which are difficult to predict and manage. Existing solutions either do not scale well under high density scenarios, or require extra communication overhead to estimate traffic density, so as to manage data dissemination accordingly. In this dissertation, we specifically aim at providing an efficient solution for the broadcast storm problem in VANETs, in order to support different types of applications. A novel approach is developed to provide scalable broadcast without extra communication overhead, by relying on traffic regime estimation using speed data. We theoretically validate the utilization of speed instead of the density to estimate traffic flow. The results of simulating our approach under different density scenarios show its efficiency in providing scalable multi-hop data dissemination for VANETs