Dynamic Event-Triggered Scheduling and Platooning Control Co-Design for Automated Vehicles Over Vehicular Ad-Hoc Networks

This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks(VANETs)subject to finite communication resource.First,a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles in the simultaneous presence of unknown external disturbances and an unknown leader control input.Under such a platoon model,the central aim is to achieve robust platoon formation tracking with desired inter-vehicle spacing and same velocities and accelerations guided by the leader,while attaining improved communication efficiency.Toward this aim,a novel bandwidth-aware dynamic event-triggered scheduling mechanism is developed.One salient feature of the scheduling mechanism is that the threshold parameter in the triggering law is dynamically adjusted over time based on both vehicular state variations and bandwidth status.Then,a sufficient condition for platoon control system stability and performance analysis as well as a co-design criterion of the admissible event-triggered platooning control law and the desired scheduling mechanism are derived.Finally,simulation results are provided to substantiate the effectiveness and merits of the proposed co-design approach for guaranteeing a trade-off between robust platooning control performance and communication efficiency.

Power Allocation for Cooperative Communications in Non-Orthogonal Cognitive Radio Vehicular Ad-Hoc Networks

To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.

A reliable and high throughput hybrid routing protocol for vehicular ad-hoc network

Due to highly dynamic topology caused by fast moving nodes the Vehicular ad-hoc network (VANET) results in the existence of transient communication links, which degrade the performance of developed protocols. Established routes frequently become stale, and existing communication flows are interrupted, incurring delay and additional overhead. In this paper we propose a novel hybrid routing protocol, which is the combined between of the table-driven routing and on-demand routing in VANET. It makes fast convergence in routing process, minimal drop links, making more reliable links, and adaptive with changing of VANET topology. With neighbor table is updated instantaneously, and using strong neighbor for routing process makes route discovery process start whenever it received requirement, and through using route mechanism appropriately it reduces significantly route overhead at each node. The simulation results illustrate the outstanding properties of our proposed routing protocol.

Dynamic Vehicular Clustering Enhancing Video on Demand Services Over Vehicular Ad-hoc Networks

Nowadays,video streaming applications are becoming one of the tendencies driving vehicular network users.In this work,considering the unpredictable vehicle density,the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load,and the limited radio range of the employed communication scheme,we introduce the“Dynamic Vehicular Clustering”(DVC)algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks(VANET).The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls,inspired by the different features and the performance of the Long Term Evolution(LTE)-Advanced network.Vehicles are clustered together to form dynamically ad-hoc sub-networks included in the vehicular network.The goal of our clustering algorithm is to take into account several characteristics,such as the vehicle’s position and acceleration to reduce latency and packet loss.Therefore,each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.Based on the exceptional features of the LTE-Advanced network(small cells and wireless backhauls)the DVC algorithm is a promising scheme for video streaming services over VANET systems.Experiments were carried out with a virtual topology of the VANET network created with four clusters to implement the DVC algorithm.The results were compared with other algorithms such as Virtual Trust-ability Data transmission(VTD),Named Data Networking(NDN),and Socially Aware Security Message Forwarding(SASMF).Our algorithm can effectively improve the transmission rate of data packets at the expense of a slight increase in end-to-end delay and control overhead.

Quantitative and qualitative correlation analysis of optimal route discovery for vehicular ad-hoc networks

Vehicular ad-hoc networks （VANETs） are a significant field in the intelligent transportation system （ITS） for improving road security. The interaction among the vehicles is enclosed under VANETs. Many experiments have been performed in the region of VANET improvement. A familiar challenge that occurs is obtaining various constrained quality of service （QoS） metrics. For resolving this issue, this study obtains a cost design for the vehicle routing issue by focusing on the QoS metrics such as collision, travel cost, awareness, and congestion. The awareness of QoS is fuzzified into a price design that comprises the entire cost of routing. As the genetic algorithm （GA） endures from the most significant challenges such as complexity, unassisted issues in mutation, detecting slow convergence, global maxima, multifaceted features under genetic coding, and better fitting, the currently established lion algorithm （LA） is employed. The computation is analyzed by deploying three well-known studies such as cost analysis, convergence analysis, and complexity investigations. A numerical analysis with quantitative outcome has also been studied based on the obtained correlation analysis among various cost functions. It is found that LA performs better than GA with a reduction in complexity and routing cost.

An Efficient Three-Factor Privacy-Preserving Authentication and Key Agreement Protocol for Vehicular Ad-Hoc Network

As an indispensable part of the Intelli-gent Transportation System(ITS),the vehicular ad-hoc network(VANET)has attracted widespread atten-tion from academia and industry.In order to ensure the security of VANET,vehicles need to be authen-ticated before accessing the network.Most existing authentication protocols in VANET adopt the Trusted Authority(TA)with centralized structure which is re-sponsible for the authentication tasks of all vehicles.However,the large-scale network consume a lot of computing resources,which leads to unacceptable de-lay in message transmission in VANET.For reducing the computational cost of TA,an efficient three-factor privacy-preserving authentication and key agreement protocol was proposed in our paper.Different from before,the RoadSide Unit(RSU)no longer acts as an intermediate node but is responsible for assisting user authentication,which lead to the computational cost of TA is very low.Through formal and informal analysis,our protocol demonstrates excellent security.Com-pared with previous studies,our work emerges advan-tages and superiorities in the following aspects:com-putational cost,communication cost,security proper-ties and functions,message loss ratio,and message de-lay.These data and evidence indicate that our protocol is an ideal choice for large-scale VANET.

Vehicle Positioning Method Based on RFID in Vehicular Ad-Hoc Networks

With the rapid development of vehicular ad hoc network( VANET) technology,VANET applications such as safe driving and emergency rescue demand high position accuracy,but traditional GPS is difficult to meet new accuracy requirements. To overcome this limitation,a new vehicle positioning method based on radio frequency identification( RFID) is proposed. First RFID base stations are divided into three categories using fuzzy technology,and then Chan algorithm is used to calculate three vehicles' positions,which are weighed to acquire vehicles' accurate position. This method can effectively overcome the problem that vehicle positioning accuracy is not high resulting from the factors such as ambient noise and base distribution when Chan algorithm is used. Experimental results show that the performance of the proposed method is superior to Chan algorithm and 2-step algorithm based on averaging method,which can satisfy the requirements of vehicle positioning in VANETs.

Effective Life and Area Based Data Storing and Deployment in Vehicular Ad-Hoc Networks

In vehicular ad-hoc networks (VANETs), store-carry-forward approach may be used for data sharing, where moving vehicles carry and exchange data when they go by each other. In this approach, storage resource in a vehicle is generally limited. Therefore, attributes of data that have to be stored in vehicles are an important factor in order to efficiently distribute desired data. In VANETs, there are different types of data which depend on the time and location. Such kind of data cannot be deployed adequately to the requesting vehicles only by popularity-based rule. In this paper, we propose a data distribution method that takes into account the effective life and area in addition to popularity of data. Our extensive simulation results demonstrate drastic improvements on acquisition performance of the time and area specific data.

Tree-Based Revocation for Certificateless Authentication in Vehicular Ad-Hoc Networks

This work proposes authentication based on identity as a way to increase the efficiency and security of communications in vehicular ad-hoc networks. When using identity-based cryptography to achieve certificateless authentication, membership revocation is not a trivial problem. Thus, in order to improve the performance of revocation in such networks, the use of a dynamic authenticated data structure based on perfect k-ary hash trees combined with a duplex version of the new standard SHA-3 is here presented. Efficient algorithms in the used revocation trees allow reaching a refresh rate of at most simple updates per inserted node. Consequently, the proposal is especially useful for situations with frequent revocations, which are foreseeable when vehicular ad- hoc networks are widely deployed.

An Intelligent Transportation System Application for Smartphones Based on Vehicle Position Advertising and Route Sharing in Vehicular Ad-Hoc Networks

Alerting drivers about incoming emergency vehicles and their routes can greatly improve their travel time in congested cities, while reducing the risk of accidents due to distractions. This paper contributes to this goal by proposing Messiah, an Android application capable of informing regular vehicles about incoming emergency vehicles like ambulances, police cars and fire brigades. This is made possible by creating a network of vehicles capable of directly communicating between them. The user can, therefore, take driving decisions in a timely manner by considering incoming alerts. Using the support of our GRCBox hardware, the application can rely on vehicular ad-hoc network communications in the 5 GHz band, being V2V （vehicle-to-vehicle） communication provided through a combination of Android-based smartphone and our GRCBox device. The application was tested in three different scenarios with different levels of obstruction, showing that it is capable of providing alerts up to 300 meters, and notifying vehicles within less than one second.

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

Lattice-Based Double-Authentication-Preventing Ring Signature for Security and Privacy in Vehicular Ad-Hoc Networks

Amidst the rapid development of the Internet of Things (loT), Vehicular Ad-Hoc NETwork (VANET), a typical loT application, are bringing an ever-larger number of intelligent and convenient services to the daily lives of individuals. However, there remain challenges for VANETs in preserving privacy and security. In this paper, we propose the first lattice-based Double-Authentication-Preventing Ring Signature (DAPRS) and adopt it to propose a novel privacy-preserving authentication scheme for VANETs, offering the potential for security against quantum computers. The new construction is proven secure against chosen message attacks. Our scheme is more efficient than other ring signature in terms of the time cost of the message signing phase and verification phase, and also in terms of signature length. Analyses of security and efficiency demonstrate that our proposed scheme is provably secure and efficient in the application.

Trust Score-Based Malicious Vehicle Detection Scheme in Vehicular Network Environments

Advancements in the vehicular network technology enable real-time interconnection,data sharing,and intelligent cooperative driving among vehicles.However,malicious vehicles providing illegal and incorrect information can compromise the interests of vehicle users.Trust mechanisms serve as an effective solution to this issue.In recent years,many researchers have incorporated blockchain technology to manage and incentivize vehicle nodes,incurring significant overhead and storage requirements due to the frequent ingress and egress of vehicles within the area.In this paper,we propose a distributed vehicular network scheme based on trust scores.Specifically,the designed architecture partitions multiple vehicle regions into clusters.Then,cloud supervision systems(CSSs)verify the accuracy of the information transmitted by vehicles.Additionally,the trust scores for vehicles are calculated to reward or penalize them based on the trust evaluation model.Our proposed scheme demonstrates good scalability and effectively addresses the main cause of malicious information distribution among vehicles.Both theoretical and experimental analysis show that our scheme outperforms the compared schemes.

Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy violations.To address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed recently.However,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many attacks.As such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)operations.The formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably secure.The proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and unlinkability.Moreover,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and impersonations.From the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security features.Therefore,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

Cybersecurity and Privacy Protection in Vehicular Networks (VANETs)

As Vehicular ad hoc networks (VANETs) become more sophisticated, the importance of integrating data protection and cybersecurity is increasingly evident. This paper offers a comprehensive investigation into the challenges and solutions associated with the privacy implications within VANETs, rooted in an intricate landscape of cross-jurisdictional data protection regulations. Our examination underscores the unique nature of VANETs, which, unlike other ad-hoc networks, demand heightened security and privacy considerations due to their exposure to sensitive data such as vehicle identifiers, routes, and more. Through a rigorous exploration of pseudonymization schemes, with a notable emphasis on the Density-based Location Privacy (DLP) method, we elucidate the potential to mitigate and sometimes sidestep the heavy compliance burdens associated with data protection laws. Furthermore, this paper illuminates the cybersecurity vulnerabilities inherent to VANETs, proposing robust countermeasures, including secure data transmission protocols. In synthesizing our findings, we advocate for the proactive adoption of protective mechanisms to facilitate the broader acceptance of VANET technology while concurrently addressing regulatory and cybersecurity hurdles.

Trust Access Authentication in Vehicular Network Based on Blockchain

Data sharing and privacy securing present extensive opportunities and challenges in vehicular network.This paper introducestrust access authentication scheme’as a mechanism to achieve real-time monitoring and promote collaborative sharing for vehicles.Blockchain,which can provide secure authentication and protected privacy,is a crucial technology.However,traditional cloud computing performs poorly in supplying low-latency and fast-response services for moving vehicles.In this situation,edge computing enabled Blockchain network appeals to be a promising method,where moving vehicles can access storage or computing resource and get authenticated from Blockchain edge nodes directly.In this paper,a hierarchical architecture is proposed consist of vehicular network layer,Blockchain edge layer and Blockchain network layer.Through a authentication mechanism adopting digital signature algorithm,it achieves trusted authentication and ensures valid verification.Moreover,a caching scheme based on many-to-many matching is proposed to minimize average delivery delay of vehicles.Simulation results prove that the proposed caching scheme has a better performance than existing schemes based on central-ized model or edge caching strategy in terms of hit ratio and average delay.

V2X Offloading and Resource Allocation in SDN-Assisted MEC-Based Vehicular Networks

As an important application scenario of 5G, the vehicular network has a huge amount of computing data, which brings challenges to the scarce network resources. Mobile edge computing(MEC) sinks cloud services to the edge of network, which reduces the delay jitter caused by remote cloud computing. Software-defined networking(SDN) is an emerging network paradigm with the features of logic centralized control and programmability. In this paper, we construct an SDN-assisted MEC network architecture for the vehicular network. By introducing SDN controller, the efficiency and flexibility of vehicular network are improved, and the network state can be perceived from the global perspective. To further reduce the system overhead, the problem of vehicle to everything(V2X) offloading and resource allocation is proposed, where the optimal offloading decision, transmission power control, subchannels assignment, and computing resource allocation scheme are given. The optimization problem is transformed into three stages because of the heterogeneity of the offloaded tasks and the NP-hard property of the problem. Firstly, the analytic hierarchy process is used to select initial offloading node, then stateless Q-learning is adopted to allocate transmission power, subchannels and computing resources. In addition, the offloading decision is modeled as a potential game, and the Nash equilibrium is proved by the potential function construction. Finally, the numerical results show that the proposed mechanism can effectively reduce the system overhead and achieve better results compared with others’ algorithms.

Mobility-Aware Partial Computation Offloading in Vehicular Networks: A Deep Reinforcement Learning Based Scheme

Encouraged by next-generation networks and autonomous vehicle systems,vehicular networks must employ advanced technologies to guarantee personal safety,reduce traffic accidents and ease traffic jams.By leveraging the computing ability at the network edge,multi-access edge computing(MEC)is a promising technique to tackle such challenges.Compared to traditional full offloading,partial offloading offers more flexibility in the perspective of application as well as deployment of such systems.Hence,in this paper,we investigate the application of partial computing offloading in-vehicle networks.In particular,by analyzing the structure of many emerging applications,e.g.,AR and online games,we convert the application structure into a sequential multi-component model.Focusing on shortening the application execution delay,we extend the optimization problem from the single-vehicle computing offloading(SVCOP)scenario to the multi-vehicle computing offloading(MVCOP)by taking multiple constraints into account.A deep reinforcement learning(DRL)based algorithm is proposed as a solution to this problem.Various performance evaluation results have shown that the proposed algorithm achieves superior performance as compared to existing offloading mechanisms in deducing application execution delay.

Edge Computing-Based Joint Client Selection and Networking Scheme for Federated Learning in Vehicular IoT

In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments.Federated learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy.However,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still under-explored.In this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular IoT.The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with environments.The clients also work as forwarder nodes in information sharing among network entities.The client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking architecture.We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.

Joint Allocation of Wireless Resource and Computing Capability in MEC-Enabled Vehicular Network

In MEC-enabled vehicular network with limited wireless resource and computation resource,stringent delay and high reliability requirements are challenging issues.In order to reduce the total delay in the network as well as ensure the reliability of Vehicular UE(VUE),a Joint Allocation of Wireless resource and MEC Computing resource(JAWC)algorithm is proposed.The JAWC algorithm includes two steps:V2X links clustering and MEC computation resource scheduling.In the V2X links clustering,a Spectral Radius based Interference Cancellation scheme(SR-IC)is proposed to obtain the optimal resource allocation matrix.By converting the calculation of SINR into the calculation of matrix maximum row sum,the accumulated interference of VUE can be constrained and the the SINR calculation complexity can be effectively reduced.In the MEC computation resource scheduling,by transforming the original optimization problem into a convex problem,the optimal task offloading proportion of VUE and MEC computation resource allocation can be obtained.The simulation further demonstrates that the JAWC algorithm can significantly reduce the total delay as well as ensure the communication reliability of VUE in the MEC-enabled vehicular network.