Networking And Security Solutions For Vanet Initial Deployment Stage

Vehicular ad hoc network (VANET) is a special case of mobile networks, where vehicles equipped with computing/communicating devices (called smart vehicles ) are the mobile wireless nodes. However, the movement pattern of these mobile wireless nodes is no more random, as in case of mobile networks, rather it is restricted to roads and streets. Vehicular networks have hybrid architecture; it is a combination of both infrastructure and infrastructure-less architectures. The direct vehicle to vehicle (V2V) communication is infrastructure-less or ad hoc in nature. Here the vehicles traveling within communication range of each other form an ad hoc network. On the other hand, the vehicle to infrastructure (V2I) communication has infrastructure architecture where vehicles connect to access points deployed along roads. These access points are known as road side units (RSUs) and vehicles communicate with other vehicles/wired nodes through these RSUs. To provide various services to vehicles, RSUs are generally connected to each other and to the Internet. The direct RSU to RSU communication is also referred as I2I communication. The success of VANET depends on the existence of pervasive roadside infrastructure and sufficient number of smart vehicles. Most VANET applications and services are based on either one or both of these requirements. A fully matured VANET will have pervasive roadside network and enough vehicle density to enable VANET applications. However, the initial deployment stage of VANET will be characterized by the lack of pervasive roadside infrastructure and low market penetration of smart vehicles. It will be economically infeasible to initially install a pervasive and fully networked iv roadside infrastructure, which could result in the failure of applications and services that depend on V2I or I2I communications. Further, low market penetration means there are insufficient number of smart vehicles to enable V2V communication, which could result in failure of services and applications that depend on V2V communications. Non-availability of pervasive connectivity to certification authorities and dynamic locations of each vehicle will make it difficult and expensive to implement security solutions that are based on some central certificate management authority. Nonavailability of pervasive connectivity will also affect the backend connectivity of vehicles to the Internet or the rest of the world. Due to economic considerations, the installation of roadside infrastructure will take a long time and will be incremental thus resulting in a heterogeneous infrastructure with non-consistent capabilities. Similarly, smart vehicles will also have varying degree of capabilities. This will result in failure of applications and services that have very strict requirements on V2I or V2V communications. We have proposed several solutions to overcome the challenges described above that will be faced during the initial deployment stage of VANET. Specifically, we have proposed: A VANET architecture that can provide services with limited number of heterogeneous roadside units and smart vehicles with varying capabilities. A backend connectivity solution that provides connectivity between the Internet and smart vehicles without requiring pervasive roadside infrastructure or large number of smart vehicles. A security architecture that does not depend on pervasive roadside infrastructure or a fully connected V2V network and fulfills all the security requirements. v Optimization solutions for placement of a limited number of RSUs within a given area to provide best possible service to smart vehicles. The optimal placement solutions cover both urban areas and highways environment

Evolution of 5G Network: A Precursor towards the Realtime Implementation of VANET for Safety Applications in Nigeria

  A crucial requirement for the successful real-time design and deployment of Vehicular Adhoc Networks (VANET) is to ensure high speed data rates, low latency, information security, and a wide coverage area without sacrificing the required Quality of Service (QoS) in VANET. These requirements must be met for flawless communication on the VANET. This study examines the generational patterns in mobile wireless communication and looks into the possibilities of adopting fifth generation (5G) network technology for real-time communication of road abnormalities in VANET. The current paper addresses the second phase of a project that is now underway to develop real-time road anomaly detection, characterization, and communication systems for VANET. The major goal is to reduce the amount of traffic accidents on Nigerian roadways. It will also serve as a platform for the real-time deployment and testing of various road anomaly detection algorithms, as well as schemes for communicating such detected anomalies in the VANET.   &nbsp

The Role of communication and network technologies in vehicular applications

International audienceVehicular networks attract a lot of attention in the research world. Novel vehicular applications need a suitable communication channel in order to extend in-vehicle capabilities and, be aware about surrounding events. However, these networks present some proprieties, such as high mobility or specific topologies. These properties affect the performances of applications and more effort should be directed to identify the final necessities of the network. Few works deal with application requirements which should be considered when vehicular services are designed. In this chapter this gap is filled, proposing an analysis of application requirements which considers available technologies for physical/MAC and network layers. This study contains key factors which must be taken into account not only at the designing stage of the vehicular network, but also when applications are evaluated

Smart Vehicles, Technologies and Main Applications in Vehicular Ad hoc Networks

Vehicular Ad hoc NETworks (VANETs) belong to a subcategory of traditional Mobile Ad hoc NETworks (MANETs). The main feature of VANETs is that mobile nodes are vehicles endowed with sophisticated “on-board” equipments, traveling on constrained paths (i.e., roads and lanes), and communicating each other for message exchange via Vehicle-to-Vehicle (V2V) communication protocols, as well as between vehicles and fixed road-side Access Points (i.e., wireless and cellular network infrastructure), in case of Vehicle-to-Infrastructure (V2I) communications. In this chapter we will introduce the state-of-the-art of recent technologies used in vehicular networks, specifically for smart vehicles, which require novel functionalities such as data communications, accurate positioning, control and decision monitoring

Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects

© 2013 IEEE. Internet of Things is smartly changing various existing research areas into new themes, including smart health, smart home, smart industry, and smart transport. Relying on the basis of 'smart transport,' Internet of Vehicles (IoV) is evolving as a new theme of research and development from vehicular ad hoc networks (VANETs). This paper presents a comprehensive framework of IoV with emphasis on layered architecture, protocol stack, network model, challenges, and future aspects. Specifically, following the background on the evolution of VANETs and motivation on IoV an overview of IoV is presented as the heterogeneous vehicular networks. The IoV includes five types of vehicular communications, namely, vehicle-to-vehicle, vehicle-to-roadside, vehicle-to-infrastructure of cellular networks, vehicle-to-personal devices, and vehicle-to-sensors. A five layered architecture of IoV is proposed considering functionalities and representations of each layer. A protocol stack for the layered architecture is structured considering management, operational, and security planes. A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs. Finally, the challenges ahead for realizing IoV are discussed and future aspects of IoV are envisioned

Physical and Link Layer Implications in Vehicle Ad Hoc Networks

Vehicle Ad hoc Networks (V ANET) have been proposed to provide safety on the road and deliver road traffic information and route guidance to drivers along with commercial applications. However the challenges facing V ANET are numerous. Nodes move at high speeds, road side units and basestations are scarce, the topology is constrained by the road geometry and changes rapidly, and the number of nodes peaks suddenly in traffic jams. In this thesis we investigate the physical and link layers of V ANET and propose methods to achieve high data rates and high throughput. For the physical layer, we examine the use of Vertical BLAST (VB LAST) systems as they provide higher capacities than single antenna systems in rich fading environments. To study the applicability of VB LAST to VANET, a channel model was developed and verified using measurement data available in the literature. For no to medium line of sight, VBLAST systems provide high data rates. However the performance drops as the line of sight strength increases due to the correlation between the antennas. Moreover, the performance of VBLAST with training based channel estimation drops as the speed increases since the channel response changes rapidly. To update the channel state information matrix at the receiver, a channel tracking algorithm for flat fading channels was developed. The algorithm updates the channel matrix thus reducing the mean square error of the estimation and improving the bit error rate (BER). The analysis of VBLAST-OFDM systems showed they experience an error floor due to inter-carrier interference (lCI) which increases with speed, number of antennas transmitting and number of subcarriers used. The update algorithm was extended to VBLAST -OFDM systems and it showed improvements in BER performance but still experienced an error floor. An algorithm to equalise the ICI contribution of adjacent subcarriers was then developed and evaluated. The ICI equalisation algorithm reduces the error floor in BER as more subcarriers are equalised at the expense of more hardware complexity. The connectivity of V ANET was investigated and it was found that for single lane roads, car densities of 7 cars per communication range are sufficient to achieve high connectivity within the city whereas 12 cars per communication range are required for highways. Multilane roads require higher densities since cars tend to cluster in groups. Junctions and turns have lower connectivity than straight roads due to disconnections at the turns. Although higher densities improve the connectivity and, hence, the performance of the network layer, it leads to poor performance at the link layer. The IEEE 802.11 p MAC layer standard under development for V ANET uses a variant of Carrier Sense Multiple Access (CSMA). 802.11 protocols were analysed mathematically and via simulations and the results prove the saturation throughput of the basic access method drops as the number of nodes increases thus yielding very low throughput in congested areas. RTS/CTS access provides higher throughput but it applies only to unicast transmissions. To overcome the limitations of 802.11 protocols, we designed a protocol known as SOFT MAC which combines Space, Orthogonal Frequency and Time multiple access techniques. In SOFT MAC the road is divided into cells and each cell is allocated a unique group of subcarriers. Within a cell, nodes share the available subcarriers using a combination of TDMA and CSMA. The throughput analysis of SOFT MAC showed it has superior throughput compared to the basic access and similar to the RTS/CTS access of 802.11

Review of Custom Grids for Updated Vehicles on VANET Simulators

VANET deployment and testing is time-consuming and costly. Simulation is a handy and less expensive alternative to real implementation as a workaround. It is required to develop accurate models in order to receive excellent results from a VANET simulation, which difficult operation owes to the complexity of the VANET infrastructure (for example, simulators have to model the navigation models and communication protocols). The network and navigation components, which are the building blocks of contemporary VANET simulators, are described in this section. Simulators are a useful tool for testing VANETs at a minimal cost and without endangering users. However, in order to be helpful and convey trustworthy findings, simulators must be able to simulate new technologies that enter the VANET and enable safety and security procedures. To put it another way, if simulation is a good tool for VANET development it should be enhanced. VANET simulators have been the subject of research since early 2010 [1-4]. They analyze the correctness of VANET's numerous tools like a navigation simulator and network simulator, as well as how these building blocks are connected. The introduction of new network technologies such as 5G, SDN, edge computing, and VANET research as a result of investments in autonomous cars is forcing VANET simulators to re-evaluate their support for these new capabilities. We present an updated evaluation of VANET simulators in this post, highlighting their key features and current support for emerging technologies