Vehicular Networks

The vehicular ad hoc network is the decentralized type of network in which vehicle nodes can join or leave the network when they want. The vehicular network is much vulnerable to security attacks which affect network performance. The active attacks are those which reduce network performance in terms of certain parameters. This paper is related to Sybil attack. The techniques which are proposed for the isolation of Sybil attack is reviewed and analyzed in this paper. The techniques are implemented in the network simulators and results are analyzed in terms of certain parameters.

New communication technologies integrated into modern vehicles offer an opportunity for better assistance to people injured in traffic accidents. Recent studies show how communication capabilities should be supported by artificial intelligence systems capable of automating many of the decisions to be taken by emergency services, thereby adapting the rescue resources to the severity of the accident and reducing assistance time. To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help emergency services better estimate the required resources. This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Our system considers the most relevant variables that can characterize the severity of the accidents (variables such as the vehicle speed, the type of vehicles involved, the impact speed, and the status of the airbag). Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models that can predict the severity of new accidents. We develop a prototype of our system based on off-the-shelf devices and validate it at the Applus+ IDIADA Automotive Research Corporation facilities, showing that our system can notably reduce the time needed to alert and deploy emergency services after an accident takes place.

Machine to machine (M2M) communications will lead to dramatic changes in the applications and services offered to citizens, allowing smart city to become a reality. In this article, we first introduce the new tendency in M2M development and analyze the construction frame of application systems in smart city. Then, an event-based architecture depending on SOFIA project is built to allow the management and cooperation among M2M components by mean of event manager. Based on this architecture, we conduct a case study in a vehicular context. M2M network architecture is introduced for vehicular networks. Finally, an event processing flow of vehicle maintenance services is designed to manage the mission-critical wireless messages.

As the rapid development of automotive telematics, modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks (VANETs) are evolving to the Internet of Vehicles (IoV), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between IoV and big data in vehicular environment, mainly on how IoV supports the transmission, storage, computing of the big data, and how IoV benefits from big data in terms of IoV characterization, performance evaluation and big data assisted communication protocol design. We then investigate the application of IoV big data in autonomous vehicles. Finally, the emerging issues of the big data enabled IoV are discussed.

The Fifth Generation (5G) networks, including the 5G Vehicular Cloud Computing (5G-VCC) systems, have evolved rapidly offering multiple services to users. The operating principles of vehicular networks, Cloud Computing (CC), Fog Computing (FC), Mobile Edge Computing (MEC) and Software Defined Networks (SDN) are applied to 5G infrastructures. In a 5G-VCC system, the vehicles are equipped with On-Board Units (OBUs) which communicate with each other as well as with Road Side Units (RSUs). Each RSU interacts with a Cloud infrastructure which offers vehicular services with strict Quality of Service (QoS) requirements, including Driver Assistance (DA), Passengers Entertainment and Information (PEnI) and Medical (MED) services. Dense deployments of 5G access networks are also implemented, called Ultra Dense Networks (UDNs), aiming to support high data rates produced by an increased number of vehicular users. In this environment, heterogeneous technologies are used to transfer the network services to vehicles. Optimal manipulation of the communication resources is required, while at the same time vehicular users should always obtain connectivity to the most appropriate network access technology, in order the constraints of the vehicular services to be satisfied. In this thesis, existing schemes for resource allocation as well as for mobility management are studied, while novel solutions are proposed for each topic.

Initially, the theoretical background of the 5G wireless networks and 5G-VCC systems is described. Subsequently, the available delivery models for providing cloud services in 5G infrastructures are mentioned, while the available 5G-VCC architectures and the communication models are presented.

Regarding the topic of the manipulation of the available network resources in 5G-VCC systems, the available Medium Access Control schemes (MAC schemes) are studied, while at the same time resource scheduling algorithms implemented at the MAC layer of 5G-VCC systems are described. Subsequently, two novel solutions are proposed to optimize the resource allocation process in modern networks. The first one is called FLS Advanced (FLSA) and optimizes the resource allocation for real-time services. Additionally, the second one is called FLS Advanced - Cross Carrier (FLSA-CC) and is specialized for LTE-Advanced (LTE-A) access networks where carrier aggregation is applied in order to provide widened bandwidth to the users. The evaluation of the proposed algorithms is performed through extended experiments. Simulation results show that the proposed algorithms outperform existing solutions.

The mobility management requirements arising at the 5G-VCC systems are also studied. As a result of this study, initially three methods for calculating the significance of the criteria affecting the mobility management are proposed, namely the Trapezoidal Fuzzy Analytical Network Process (TF-ANP), the Trapezoidal Fuzzy Adaptive Analytical Network Process (TF-AANP) and the Pentagonal Fuzzy Analytical Network Process (PF-ANP). Subsequently, three network selection algorithms are proposed, namely the Trapezoidal Fuzzy TOPSIS (TFT), the Trapezoidal Fuzzy TOPSIS with Adaptive Criteria Weights (TFT-ACW) and the Pentagonal Fuzzy TOPSIS (PFT). Following this study and regarding the research results of the implemented algorithms, a mobility management scheme is proposed. This scheme takes into consideration the Signal to Noise plus Interference (SINR) parameters as well as the velocity of the vehicular users to evaluate the necessity of performing a handover. Then, it applies the PFT algorithm to select the most appropriate network for the user. Experimental results showed that the proposed scheme outperforms the existing solutions described in the research literature.

Data offloading using vehicles is one of the most challenging tasks to perform due to the high mobility of vehicles. There are many solutions available for this purpose, but due to the inefficient management of data along with the control decisions, these solutions are not adequate to provide data offloading by making use of the available networks. Moreover, with the advent of 5G and related technologies, there is a need to cope with high speed and traffic congestion in the existing infrastructure used for data offload-ing. Hence, to make intelligent decisions for data offloading, an SDN-based scheme is presented in this article. In the proposed scheme, an SDN-based controller is designed that makes decisions for data offloading by using the priority manager and load balancer. Using these two managers in SDN-based controllers, traffic routing is managed efficiently even with an increase in the size of the network. Moreover, a single-leader multi-follower Stackelberg game for network selection is also used for data offloading. The proposed scheme is evaluated with respect to several parameters where its performance was found to be superior in comparison to the existing schemes.

Traffic management, road safety, and environmental impact are important issues in the modern world. These challenges are addressed by the application of sensing, control and communication methods of intelligent transportation systems (ITS). A part of ITS is a vehicular ad-hoc network (VANET) which means a wireless network of vehicles. However, communication among vehicles in a VANET exposes several security threats which need to be studied and addressed. In this review, firstly, the basic flow of VANET is illustrated focusing on its communication methods, architecture, characteristics, standards, and security facilities. Next, the attacks and threats for VANET are discussed. Moreover, the authentication systems are described by which vehicular networks can be protected from fake messages and malicious nodes. Security threats and counter measures are discussed for different remote vehicle communication methods namely, remote keyless entry system, dedicated short range communication, ...

The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system. Keywords: Cloud Infotainment system Internet of vehicle Vehicular adhoc network Vehicular network

Determining how to structure vehicular network environments can be done in various ways. Here, we highlight vehicle networks’ evolution from vehicular ad-hoc networks (VANET) to the internet of vehicles (IoVs), listing their benefits and limitations. We also highlight the reasons in adopting wireless technologies, in particular, IEEE 802.11p and 5G vehicle-to-everything, as well as the use of paradigms able to store and analyze a vast amount of data to produce intelligence and their applications in vehicular environments. We also correlate the use of each of these paradigms with the desire to meet existing intelligent transportation systems’ requirements. The presentation of each paradigm is given from a historical and logical standpoint. In particular, vehicular fog computing improves on the deficiences of vehicular cloud computing, so both are not exclusive from the application point of view. We also emphasize some security issues that are linked to the characteristics of these paradigms and vehicular networks, showing that they complement each other and share problems and limitations. As these networks still have many opportunities to grow in both concept and application, we finally discuss concepts and technologies that we believe are beneficial. Throughout this work, we emphasize the crucial role of these concepts for the well-being of humanity.

Vehicular Ad hoc Networks (VANETs) have gained considerable attention in the past few years due to their promising applicability in relation to the Intelligent Transportation Systems (ITSs). This emerging new technology will provide timely information to develop adaptive traffic light control systems that will allow a significant optimization of the vehicular traffic flow. In this paper, we introduce a novel algorithm for counting vehicles stopped at a traffic light using VANET technology. The algorithm is based on the idea of the propagation of a count request message from the RSU (originating unit) toward the vehicles that are at the end of the waiting line, and the propagation of a response message (with the number of vehicles counted) in the opposite direction, that is, from the vehicles at the end of the line toward the RSU. For this, our algorithm uses BEACON messages periodically to exchange the necessary information between any two 1-hop neighbors. Using the data received from BEACON messages, each vehicle can maintain its own neighbors list. To validate and evaluate the performance of our proposal, we use Veins (Vehicle in Network Simulation) and TraCI (Traffic Control Interface). The former is a framework that ties together a network simulator (OMNeT++) with a road traffic simulator (SUMO), and the latter is an API for the communications between both simulators by providing TCP connections between each other. The results of the simulations performed in different scenarios are encouraging since they indicate that the proposed algorithm efficiently computes a number of vehicles very close to the real one, using a few control messages.

International conference on AI, Machine Learning in Communications and Networks (AIMLNET 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Machine Learning impacts on Communications and Networks. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning and networks in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and
practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

En este artículo se realiza una propuesta para el costado nor-oriente de San Salvador, referido a las Calles 5 de Noviembre y 25 Calle Poniente en el tramo comprendido entre la Carretera Troncal del Norte y la Avenida Monseñor Oscar Arnulfo Romero y Galdámez.

Clustering is a technique used in network routing to enhance the performance and conserve the network resources. This paper presents a cluster-based routing protocol for VANET utilizing a new addressing scheme in which each node gets an address according to its mobility pattern. Hamming distance technique is used then to partition the network in an address-centric manner. The simulation results show that this protocol enhances routing reachability, whereas reduces routing end-to-end delay and traffic received comparing with two benchmarks namely AODV and DSDV.

Traffic management, road safety, and environmental impact are important issues in the modern world. These challenges are addressed by the application of sensing, control and communication methods of intelligent transportation systems (ITS). A part of ITS is a vehicular ad-hoc network (VANET) which means a wireless network of vehicles. However, communication among vehicles in a VANET exposes several security threats which need to be studied and addressed. In this review, firstly, the basic flow of VANET is illustrated focusing on its communication methods, architecture, characteristics, standards, and security facilities. Next, the attacks and threats for VANET are discussed. Moreover, the authentication systems are described by which vehicular networks can be protected from fake messages and malicious nodes. Security threats and counter measures are discussed for different remote vehicle communication methods namely, remote keyless entry system, dedicated short range communication, ...

A Vehicular Ad Hoc Network (VANET) is a network formed purely among vehicles without presence of any communication infrastructure as base stations and/or access point. Frequent topological changes due to high mobility is one of the main issues in VANETs. In this paper we evaluate Ad-hoc On-Demand Distance Vector (AODV) and Optimized Link State Routing (OLSR) routing protocols using 802.11a and 802.11p in a realistic urban scenario. For this comparison, we chose five performance metrics: Path Availability, End-to-End Delay, Number of Created Paths, Path Length and Path Duration. Simulation results show, that for most of the metrics evaluated, OLSR outperforms AODV when 802.11p and that 802.11p is more efficient in urban VANETs.

Providing real-time cloud services to Vehicular Clients (VCs) must cope with delay and delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small-size self-powered data centers (e.g., Fog nodes) between remote Clouds and VCs, in order to deliver data-dissemination real-time services to the connected VCs. Motivated by these considerations, in this paper, we propose and test an energy-efficient adaptive resource scheduler for Networked Fog Centers (NetFCs). They operate at the edge of the vehicular network and are connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. The goal is to exploit the locally measured states of the TCP/IP connections, in order to maximize the overall communication-plus-computing energy efficiency, while meeting the application-induced hard QoS requirements on the minimum transmission rates, maximum delays and delay-jitters. The resulting energy-efficient scheduler jointly performs: (i) admission control of the input traffic to be processed by the NetFCs; (ii) minimum-energy dispatching of the admitted traffic; (iii) adaptive reconfiguration and consolidation of the Virtual Machines (VMs) hosted by the NetFCs; and, (iv) adaptive control of the traffic injected into the TCP/IP mobile connections. The salient features of the proposed scheduler are that: (i) it is adaptive and admits distributed and scalable implementation; and, (ii) it is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rates of the traffic delivered to the vehicular clients, instantaneous rate-jitters and total processing delays. Actual performance of the proposed scheduler in the presence of: (i) client mobility; (ii) wireless fading; and, (iii) reconfiguration and consolidation costs of the underlying NetFCs, is numerically tested and compared against the corresponding ones of some state-of-the-art schedulers, under both synthetically generated and measured real-world workload traces.

Recent research studies prove that contention-based forwarding (CBF) algorithms are preferable in highly- dynamic vehicular environments. CBF algorithms are beaconless, whereas position-based algorithms rely on periodic beacon information to make forwarding decisions. Considering the store-carry-forward paradigm of delay-tolerant networks, which relies on mobility of vehicles to deliver packets when next forwarding vehicle is unreachable, we proposed a new recovery strategy and enhanced the CBF algorithm to tackle the network disconnection problem that frequently occurs in vehicular wireless networks. This enhanced CBF with a store-carry-forward capability is referred to as CBF-SCF algorithm. The algorithm was simulated, and the results indicate that CBF-SCF outperforms normal CBF in terms of packet delivery ratio and routing overhead.

Machine to machine (M2M) communications will lead to dramatic changes in the applications and services offered to citizens, allowing smart city to become a reality. In this article, we first introduce the new tendency in M2M development and analyze the construction frame of application systems in smart city. Then, an event-based architecture depending on SOFIA project is built to allow the management and cooperation among M2M components by mean of event manager. Based on this architecture, we conduct a case study in a vehicular context. M2M network architecture is introduced for vehicular networks. Finally, an event processing flow of vehicle maintenance services is designed to manage the mission-critical wireless messages.

Abstract: A vehicular ad hoc network (VANET) uses cars as mobile nodes in a MANET to create a mobile network. For security Vehicular ad hoc networks (VANETs) adopt the Public Key Infrastructure (PKI) and Certificate Revocation Lists (CRLs). In the Public Key Infrastructure system the authentication of a received message is performed by checking if the certificate of the sender is included in the current Certificate Revocation Lists (CRLs) and verifying the authenticity of the certificate and signature of the sender. But it takes more time for CRL checking process. So in order to overcome this problem we use an efficient revocation check process in EMAP uses a keyed Hash Message Authentication Code(HMAC) , where the key used in calculating the HMAC is shared only between non-revoked On-Board Units (OBUs). In addition, EMAP uses a novel probabilistic key distribution which enables non-revoked OBUs to securely share and update a secret key. To conquer computation overhead we introduce the data aggregation using probabilistic checking that can accelerate message verifications and significantly reduce computational overhead while retaining satisfactory security.
Keywords: Vehicular networks, communication security, message authentication, certificate revocation, data aggregation.
Title: EXPEDITE MESSAGE AUTHENTICATION PROTOCOL FOR VANETs USING DATA AGGREGATION
Author: Shaiba Wahab, Jemsheer Ahmed P
International Journal of Computer Science and Information Technology Research
ISSN 2348-120X (online), ISSN 2348-1196 (print)
Research Publish Journals

Unmanned Areal Vehicles (UAVs) can be employed for temporary missions with flight ability while exposing limited flight time due to restricted battery life. To perform an efficient mission execution, UAVs must be recharged in a fixed give places. For designing the energy efficient UAV systems in Wireless Sensor Network (WSN) environment, optimizing their flight paths in large geographical areas is important for the energy-saving of UAVs. In this paper, we propose a method for optimization of Multi-UAV flight path. We consider the UAV path length that can directly affect the energy consumption for mission execution. Hence, we aim to minimize the energy consumption of UAVs in WSN. Specifically, we optimize the trajectories of multiple UAVs, where a Multiple Traveling Salesman Problem (MTSP) based path planning algorithm is proposed. The algorithm is NP-hard. Therefore, we use a Geometric Solution based on using Held Karp lower bound. Finally, we proposed a heuristic evolutionary algorithm namely Particle Swarm Optimization (PSO). Under this analysis of our experimental results, we proved that our solution is feasible.

An advanced growth in Intelligent Transportation System (ITS) has made Vehicular Ad-hoc Network (VANET) an area of exploration in academic and industrial levels. In Intelligent Transportation System each vehicle acts as a sender, receiver and forwarding router which broadcast safety and non-safety information across the network. The three major classes of applications are classified in VANET are safety oriented, convenience oriented and infotainment oriented. Main focus in this literature is based on assistance oriented applications like providing information about vacant parking spaces to the drivers who are cruising for it around their destination.

Vehicular ad hoc networks VANETs has recently received significant attention in intelligent transport systems (ITS) research. It provides the driver with information regarding traffic and road conditions which is needed to reduce accidents, which will save many people's lives. In Vehicle-to-vehicle V2V communication the high-speed mobility of the nodes is the challenge, which significantly affects the reliability of communication. In this paper the utilising of SCM-MIMO channel model, (which is based on V-BLAST channel coding) is present to evaluate the performance of the PHY layer in V2V communication. The simulation results observed that the SCM model can overcome the propagation issues such as path loss, multipath fading and shadowing loss. The simulation considered three different environments, high, medium and low disruptions in urban traffic.

Vehicle traffic congestion leads to air pollution, driver frustration, and costs billions of dollars annually in fuel consumption. Finding a proper solution to vehicle congestion is a considerable challenge due to the dynamic and unpredictable nature of the network topology of vehicular environments, especially in urban areas. Instead of using static algorithms, e.g. Dijkstra and A*, we present a bio-inspired algorithm, food search behavior of ants, which is a promising way of solving traffic congestion in vehicular networks. We have called this the ant-based vehicle congestion avoidance system (AVCAS). AVCAS combines the average travel speed prediction of traffic on roads with map segmentation to reduce congestion as much as possible by finding the least congested shortest paths in order to avoid congestion instead of recovering from it. AVCAS collects real-time traffic data from vehicles and road side units to predict the average travel speed of roads traffic. It utilizes this information to perform an ant-based algorithm on a segmented map resulting in avoidance of congestion. Simulation results conducted on various vehicle densities show that the proposed system outperforms the existing systems in terms of average travel time, which decreased by an average of 11.5%, and average travel speed which increased by an average of 13%. In addition, AVCAS handles accident conditions in a more efficient way and decreases congestion by using alternative paths.

A new kind of ad hoc network is hitting the streets: Vehicular Ad Hoc Networks (VANets). In these networks, vehicles communicate with each other and possibly with a roadside infrastructure to provide a long list of applications varying from transit safety to driver assistance and Internet access. In these networks, knowledge of the real-time position of nodes is an assumption made by most protocols, algorithms, and applications. This is a very reasonable assumption, since GPS receivers can be installed easily in vehicles, a number of which already comes with this technology. But as VANets advance into critical areas and become more dependent on localization systems, GPS is starting to show some undesired problems such as not always being available or not being robust enough for some applications. For this reason, a number of other localization techniques such as Dead Reckoning, Cellular Localization, and Image/Video Localization has been used in VANets to overcome GPS limitations. A common procedure in all these cases is to use Data Fusion techniques to compute the accurate position of vehicles, creating a new paradigm for localization in which several known localization techniques are combined into a single solution that is more robust and precise than the individual approaches. In this paper, we further discuss this subject by studying and analyzing the localization requirements of the main VANet applications. We then survey each of the localization techniques that can be used to localize vehicles and, finally, examine how these localization techniques can be combined using Data Fusion techniques to provide the robust localization system required by most critical safety applications in VANets.

Most applications developed for vehicular environments rely on broadcasting as the main mechanism to disseminate their messages. However, in IEEE 802.11p, which is the most widely accepted Medium Access Control (MAC) protocol for vehicular communications, all transmissions remain unacknowledged if broadcasting is used. Furthermore, safety message transmission requires a strict delay limit and a high reliability, which is an issue for random access MAC protocols like IEEE 802.11p. Therefore, transmission reliability becomes the most important issue for broadcast-based services in vehicular environments. In this paper, we propose a hybrid MAC protocol, referred as Dynamic Token-Based MAC Protocol (DTB-MAC). DTB-MAC uses both a token passing mechanism and a random access MAC protocol to prevent channel contention as much as possible, and to improve the reliability of safety message transmissions. Our proposed protocol tries to select the best neighbouring node as the next transmitter, and when it is not possible, or when it causes a high overhead, the random access MAC protocol is used instead. Based on simulation experiments, we show that the DTB-MAC protocol can achieve better performance compared with IEEE 802.11p in terms of channel utilization and beacon delivery ratio.

Vehicular Ad hoc network (VANET) has recently been attracting the attention of researchers as a new technology in the wireless communication system. Vehicle-to-vehicle V2V communication can be considered an important way to help the drivers to satisfy requirements such as less congestion, accident warning, road exploration, etc. The propagation issues such as multipath fading significantly affect the reliability of V2V communication. The goal of this work is to enhance the performance of the physical layer PHY in V2V communication. However, the cellular phone channel has been used to evaluate the possibility of apply it in the vehicular communication V2V. The simulation results observed that the transmitted signal is affected by a multipath fading channel. In order to overcome this problem two techniques are used: Orthogonal Frequency Division Multiplexing (OFDM) technique and Multiple-Input-Multiple-Output (MIMO) diversity technique. The simulation results showed that the OFDM technique overcomes the multipath fading with high transmission power. On the other hand, MIMO diversity technique called Alamouti Space-Time Code for two transmitters and two receivers (MIMO 2x2) is used to improve the error degradation with less transmission power.

Vehicular Ad hoc Networks (VANETs) are recognized as an important component of the Intelligent Transportation Systems. Thanks to this emerging technology, new information will be available to design better adaptive traffic light control systems which will dramatically improve the traffic flow. In this paper, we present a novel VANETbased approach to obtain (1) the position of the last vehicle and (2) the number of vehicles, in a line of vehicles stopped at a traffic light. We also show that our algorithm to estimate the position of the last vehicle will still function even if just a few vehicles are equipped with VANET technology (low penetration rate), which is important since it will take years for all vehicles to be equipped with VANET technology.

MU-MIMO (Multi-User MIMO) has been a promising technique for vehicular networks to achieve faster communication. Conventional MU-MIMO transceiver is designed with One-dimensional (1-D) improper modulation schemes such as Binary Phase Shift Keying (BPSK) and Multilevel Amplitude Shift Keying (M-ASK) failed to yield standard ABER (average bit error rate). To achieve high reliability, a novel MU-MIMO uplink transceiver system is designed under PAPC (Per-Antenna Power Constraint) by assuming perfect and imperfect channel state information (CSI). MIMO communication channels are perceptible. Hence, security of the proposed system is improved by novel pseudorandom key generation technique using randomized synthetic colour image. Analytical design for proposed systems is carried and simulated for various p-norm constraints. Simulation results show higher reliability and security than the existing system. It also satisfies the linearity constraint of a power amplifier, which makes the system more suitable for practical applications.

assistance to people injured in traffic accidents. Recent studies show how communication capabilities should be supported by artificial intelligence systems capable of automating many of the decisions to be taken by emergency services, thereby adapting the rescue resources to the severity of the accident and reducing assistance time. To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help the emergency services to better estimate the required resources. This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Our system considers the most relevant variables that can characterize the severity of the accidents (variables such as the vehicle speed, the type of vehicles involved, the impact speed, and the status of the airbag). Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models able to predict the severity of new accidents.

Vehicular communication systems (VCS) are becoming a cornerstone of modern intelligent transport systems. By enabling vehicles to communicate with each other via intervehicle communication as well as with roadside units via roadside-to-vehicle communication, vehicular networks will contribute to safer and more efficient roads by providing timely information to drivers and concerned authorities. This paper develops a new vehicular communication architecture supporting a wide spectrum of applications. We analyze the security services provided by this architecture and focus on event timestamping, which is of great interest in incident investigation. Our major contribution is the introduction of a new component, called the black box, which is able to securely store the events related to the vehicle. We also develop a new cryptographic protocol to support the management of the black box component.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5345385

It is noticeable that most of VANETs communications tests are assessed through simulation. In a majority of simulation results, the physical layer is often affected by an apparent lack of realism. Therefore, vehicular channel model has become a critical issue in the field of intelligent transport systems (ITS). To overcome the lack of realism problem, a more robust channel model is needed to reflect the reality. This paper provides an open access, predefined channel coefficients library. The library is based on 2x2 and 4x4 Multiple Input Multiple Output (MIMO) systems in V2V communications, using a spatial channel model extended SCME which will help to reduce the overall simulation time. In addition, it provides a more realistic channel model for V2V communications; considering: over ranges of speeds, distances, multipath signals, sub-path signals, different angle of arrivals, different angle departures, no line of sight and line of sight. An intensive evaluation process has taken place to validate the library and acceptance results are produced. Having an open access predefined library, enables the researcher at relevant communities to test and evaluate several complicated vehicular communications scenarios in a wider manners with less time and efforts.

Vehicular Ad hoc Networks (VANETs) are recognized as an important component of the Intelligent Transportation Systems. Thanks to this emerging technology, new information will be available to design better adaptive traffic light control systems which will dramatically improve the traffic flow. In this paper, we present a novel VANETbased approach to obtain (1) the position of the last vehicle and (2) the number of vehicles, in a line of vehicles stopped at a traffic light. We also show that our algorithm to estimate the position of the last vehicle will still function even if just a few vehicles are equipped with VANET technology (low penetration rate), which is important since it will take years for all vehicles to be equipped with VANET technology.

There is a strong devotion in the automotive industry to be part of a wider progression towards the Fifth Generation (5G) era. In-vehicle integration costs between cellular and vehicle-to-vehicle networks using Dedicated Short Range Communication could be avoided by adopting Cellular Vehicle-to-Everything (C-V2X) technology with the possibility to re-use the existing mobile network infrastructure. More and more, with the emergence of Software Defined Networks, the flexibility and the programmability of the network have not only impacted the design of new vehicular network architectures but also the implementation of V2X services in future intelligent transportation systems. In this paper, we define the concepts that help evaluate software-defined-based vehicular network systems in the literature based on their modeling and implementation schemes. We first overview the current studies available in the literature on C-V2X technology in support of V2X applications. We then present the ...

In the recent year's vehicular ad hoc networks VANETs has received significant attention in the intelligent transport system research. Vehicle-to-vehicle V2V communication can be considered an important approach to help the drivers to satisfy requirements like less congestion, accident warning, road exploration, etc. The propagation issues such as path loss, multipath fading, shadowing loss, depolarization loss, and polarization mismatch loss significantly affect the reliability of V2V communication. The goal of this paper is to evaluate the performance of the PHY layer in V2V communication using a modified Spatial Channel Model SCM-MIMO. The simulation results observed that the transmitted signal is affected by a multipath fading channel.

Efficient data dissemination is a key of successful Vehicular Ad Hoc Networks (VANETs) applications. In VANETs, one of the main challenges is how to overcome the intermittent vehicle-to-vehicle connectivity problem. Secondly, how to increase the connecting possibility in the sparse environment (during off peak hour, highway etc.). Placing Road Side Units (RSUs) along roadside acting as a buffer point, is one of the solutions proposed, recently. However, each RSU has limited bandwidth and coverage range. During rush hours an RSU might be overloaded by the passing vehicles. This endures a higher request drop rate in the overloaded RSUs. In our previous work we have proposed a cooperative load balancing (CLB) solution to handle this situation. In this paper, we investigate that with the prior knowledge of other RSUs' locations and the final destination, the system performance further can be improved significantly. We propose a modified CLB (MCLB) approach in this paper. A number of simulation experiments demonstrate the superiority of the MCLB approach over the CLB and the standalone approaches.

By exchanging events in a vehicular ad hoc network (VANET), drivers can receive interesting information while driving. For example, they can be informed of available parking spaces in their vicinity. A suitable protocol is needed to disseminate the events efficiently within the area where they are relevant. Moreover, in such a competitive context where each vehicle may be interested in a resource, it is crucial not to communicate that resource to each driver in the vicinity. Otherwise, those drivers would waste time trying to reach a parking space and only one of them would be fulfilled, which would lead to a poor satisfaction in the system.

Data transport fluctuations affecting vehicular connectivity are inexperienced in fixed access as well as in pedestrian mobility: in this paper we review how solutions known as WAN (wide area network) optimizations can be effective to improve user experience in vehicular clients.  We show that the core techniques for enabling WAN optimizations are based on network traffic predictions and can largely benefit from fusion of information available from other vehicular subsystems like GPS navigation.
We argue that a suitable platform for implementing vehicular connectivity consists of commodity LTE (long term evolution) access points docked into properly programmed PLDs (programmable logic devices).