Security in V2I Communications: A Systematic Literature Review.

DIVINE: Data offloading in vehicular networks with QoS provisioning

With the adoption of sensing technology, vehicles are able to gather information about driver's environment, like speed, temperature, moisture and road condition, etc. The state-of-the-art wireless technologies also provide vehicles with the ability of communicating to their neighboring vehicles on the road, as well as the static frameworks on the road side. Vehicular Sensor Network (VSN) is an emerging paradigm in vehicular networks. In this paper, we propose a new VSN scenario, Road Probing. The Road Side Unit (RSU) initiates the probing process and selects the passing by vehicles as probes to collect traffic and environment information. The selected vehicles sense the desired data and forward it back to the RSU in a multi-hop fashion. A dynamically growing one-dimension probing chain originated from the RSU is formed by participated vehicles as the probing process going on. A mobility profile based probe selection method is developed to improve this chain's connectivity as it's the key issue to assure the quality of data collection. The performance of Road Probing is demonstrated by simulation experiments.

With the development of the vehicular communications technology, roadside units (RSUs) placement problem has recently received considerable attentions in vehicular ad hoc networks (VANETs). This paper addresses the roadside units (RSUs) placement problem for traffic flow coverage requirement number in vehicular ad hoc networks (VANETs). Given a set of road segments, some traffic flows and a coverage requirement number n, the problem is how to find the optimal placement of RSUs, such that each traffic flow is covered by at least n RSUs. We first investigate full RSUs placement problem, which place all the RSUs on the given road segments totally. We prove that this problem is NP-hard. Then, we propose a greedy algorithm to solve the problem and theoretical analysis is given. We also study incremental RSUs placement problem, which place the partial RSUs based on the deployed RSUs on the given road segments. Based on the proposed greedy algorithm, we also propose a algorithm to solve the incremental RSUs placement problem. Extensive simulations have been conducted to show the performance of our proposed algorithms is superior to the other algorithms.

The reliability of communication in vehicular networks depends mostly on the density of DSRC-enabled vehicles that form the network. In highway scenarios, and depending on the time of day, the probability of having a disconnected vehicular network can be very high, which hinders communication reliability. To improve communication in these scenarios, infrastructure points known as Road Side Units (RSU) may be used. RSUs, however, have an associated cost, and therefore the number of RSUs needs to be minimized while still providing a significant improvement on communications. In this paper we study the effect of including RSUs as relay nodes to improve communication in highway scenarios. We model the average time taken to propagate a packet to disconnected nodes (denoted as re-healing time) when considering both scenarios of connected and disconnected RSUs. We then compare the results of both these models and of a model with no RSUs. Results show significant improvements with RSU deployments, both connected and disconnected, particularly in multi-cluster communication scenarios.

Orthogonal time frequency space (OTFS) modulation is a promising candidate for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we consider the employment of the integrated (radar) sensing and communication (ISAC) technique for assisting OTFS transmission in both uplink and downlink vehicular communication systems. Benefiting from the OTFS-ISAC signals, the roadside unit (RSU) is capable of simultaneously transmitting downlink information to the vehicles and estimating the sensing parameters of vehicles, e.g., locations and speeds, based on the reflected echoes. Then, relying on the estimated kinematic parameters of vehicles, the RSU can construct the topology of the vehicular network that enables the prediction of the vehicle states in the following time instant. Consequently, the RSU can effectively formulate the transmit downlink beamformers according to the predicted parameters to counteract the channel adversity such that the vehicles can directly detect the information without the need of performing channel estimation. As for the uplink transmission, the RSU can infer the delays and Dopplers associated with different channel paths based on the aforementioned dynamic topology of the vehicular network. Thus, inserting guard space as in conventional methods are not needed for uplink channel estimation which removes the required training overhead. Finally, an efficient uplink detector is proposed by taking into account the channel estimation uncertainty. Through numerical simulations, we demonstrate the benefits of the proposed ISAC-assisted OTFS transmission scheme.

The recent advances in wireless communication techniques have made it possible for fast-moving vehicles to download data from the Internet. For the reliable data upload and download, TCP can be used for vehicular networks. However, TCP requires the connection initialization using three-way handshaking for the data exchange between two end systems over the Internet. Thus, the efficient operation of TCP is important for data services in the vehicular networks. This paper proposes a method of TCP Context Migration Scheme (TOMS) for the enhancement of data services in vehicular networks. TOMS provides vehicles with proactive TCP connection initialization using a moving TCP proxy as a cluster head, which will have the Internet connectivity with a Road-Side Unit (RSU). A cluster member can initiate its TCP connection toward its corresponding TCP end-system (e.g., server and peer) via the TCP proxy within its cluster. The TCP proxy performs the TCP connection set-up for the sake of other cluster member vehicles and acknowledges the received TCP segments toward these vehicles. When the TCP proxy moves out of the communication range of the RSU, it transfers the TCP contexts of other vehicles to another vehicle, which will play the role of a TCP proxy through the proposed TCP context migration scheme. Also, the RSU works as a fixed TCP proxy for handling the acknowledgement of TCP segments and TCP timer handling (e.g., persist timer and keepalive timer) when there happens the disconnection between the moving proxy and the RSU. Thus, it is shown that our TOMS outperforms the legacy TCP in vehicular networks.

Since most of vehicular radar systems are already exploiting millimeter-wave (mmWave) spectra, it would become much more feasible to implement a joint radar and communication system by extending communication frequencies into the mmWave band. In this paper, an IEEE 802.11ad waveform-based radar imaging technique is proposed for vehicular settings. A roadside unit (RSU) transmits the IEEE 802.11ad waveform to a vehicle for communications while the RSU also listens to the echoes of transmitted waveform to perform inverse synthetic aperture radar (ISAR) imaging. To obtain high-resolution images of the vehicle, the RSU needs to accurately estimate round-trip delays, Doppler shifts, and velocity of vehicle. The proposed ISAR imaging first estimates the round-trip delays using a good correlation property of Golay complementary sequences in the IEEE 802.11ad preamble. The Doppler shifts are then obtained using least square estimation from the echo signals and refined to compensate phase wrapping caused by phase rotation. The velocity of vehicle is determined using an equation of motion and the estimated Doppler shifts. Simulation results verify that the proposed technique is able to form high-resolution ISAR images from point scatterer models of realistic vehicular settings with different viewpoints. The proposed ISAR imaging technique can be used for various vehicular applications, e.g., traffic condition analyses or advanced collision warning systems.

This paper proposed a mobility-aware multimedia data transfer mechanism using Multipath TCP in Vehicular Network. Since high transmission rate and low latency are the two key factors for multimedia data transmission that could provide stable video streaming services, therefore, we first adopted Multipath Transport Control Protocol which can transfer data concurrently for improving transmission rate and designed Quality-aware Data Distribution to dynamically allocate the data to different subflows. Moreover, in Vehicular Network, the mobile terminal, which means the vehicle, can communicate with remote server through roadside unit (RSU). However, the communication link between terminals and remote server will disrupt while the vehicle exceeding the communication range of roadside unit; and there also exists the situation that the vehicle is in the communication range of several RSU. Accordingly, we exploited a mobility-aware distance measurement for checking whether the vehicle has moved out of the communication range of any RSU or it is in multi-RSU's communication range. Afterwards, we designed a handover mechanism which transfer data to connected path (4G) for stable transmission using MPTCP when the vehicle exceeded the communication range of RSU; while one mobile can communicate with more than one RSU, we exploited a mechanism which can trigger new path for multipath data transmission and non-corporation Nash Equilibria was employed for solving the problem of fairness in the same kind of network technology multipath transmission. Simulation results show how mobility-aware multimedia data transfer mechanism improve the performance of transmission comparison with state-of-art solution.

Vehicular Ad-hoc Network (VANET) is critical for intelligent transportation, enabling vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication to enhance road safety and efficiency. However, existing protocols face challenges such as security issues, high computational overhead and single-point-of-failure risks in V2I communication. In response to these challenges, we propose a lightweight anonymous authenticated key agreement protocol supported by a multi-Trusted Authority (TA) model, using hash functions and XOR operations to achieve mutual authentication between vehicles and Road Side Unit (RSU), as well as between RSU and TA, while establishing secure session key. Performance evaluation shows it has lower computational overhead and meets many security requirements, outperforming existing schemes in efficiency and security for intelligent transportation systems.

A deep learning based misbehavior classification scheme for intrusion detection in cooperative intelligent transportation systems

In this work, we propose a new GRASP-based heuristic, called ΔrGRASP2_MH, for solving the allocation of roadside units (RSUs) in a vehicular network with multi-hop transmission and synchronous communication. A vehicular network with hybrid architecture enables the infrastructure-to-vehicle communication, as well as the vehicle- to-vehicle communication. Our goal is to find the minimum set of RSUs to meet the quality of service requirements specified by the Deployment Δρ1ρ2. The Deployment Δρ1ρ2 is a metric employed in the evaluation of the quality of service offered in vehicular networks. We test ΔrGRASP2_MH under several communication ranges to analyze the influence exerted by these ranges on the number of RSUs employed.

Vehicular communication is one of the critical technologies in intelligent transportation system to provide connectivity between vehicles, road side units, and pedestrians. Multiple wireless accessing technologies designed to provide connectivity in vehicular networks such as conventional Wi-Fi, IEEE 802.11p, and cellular communications. Recently, cellular V2X (C-V2X) is standardized and designed by the third generation partnership project (3GPP) for automotive services. C-V2X supports two communication modes through a single platform to provide both Wi-Fi and cellular communication. LTE-V2X is the current 3GPPRelease 14 standard that has many enhancements to provide the new 3GPPRelease 16 for the new 5G radio generation. 5G-new radio (NR) is expected to address the automotive capabilities, improvement, and services for 2020 and beyond. 5G-NR becomes a competitive technology compared with other wireless technologies because of extensive coverage, high capacity, high reliability, and low delay support. In this paper, we propose the Optimizing of 5G with V2X, and analyzing the current V2X standards, introducing the development of 5G, challenges, features, requirements, design, and technologies.

The new era of the Internet of Things is promoting the evolution of self-driving vehicles into connected and autonomous vehicles (CAVs), which enable modern intelligent transportation systems. CAVs provide connectivity for vehicles by integrating the capabilities of new generation wireless technologies such as dedicated short-range communication (DSRC) and cellular networks (e.g., LTE, 5G, and potential future 6G developments). The success of CAVs and their applications is dependent on the performance of their underlying networks, known as vehicular networks, which can be compromised due to the traffic dynamics and limited transmission range of communication devices. This dissertation focuses on the optimization of message coverage and dissemination that improves the overall performance of vehicular networks. The coverage of message, from a performance perspective, can be studied in terms of dissemination distance, the size of inter-vehicle networks, and the delay of message dissemination. We study the message coverage in infrastructure-based vehicular networks by focusing on the problem of optimal utilization of roadside units (RSUs) in urban environments. Specifically, we develop efficient algorithms, which by considering the driving dynamics and delay constraint of applications find the candidate sites for RSUs deployment to achieve the maximum spatiotemporal message coverage and minimum delay of message dissemination. We also present a disseminator selection algorithm for infrastructure-based environments, which aims at improving message forwarding in the presence of RSUs. Effective clustering is crucial to mitigate routing scalability and reliability issues in vehicular networks. Clustering provides a hierarchical network architecture as a result of grouping the vehicles. We propose an adaptive clustering scheme to maximize the stability of clusters. To that end, we define a novel concept, named stability degree of vehicles, by taking into consideration the driving dynamics over a prediction horizon. We then formulate the clustering problem as an optimization problem, which is used within a rolling horizon framework in the cluster formation process. Our scheme also provides insight into the optimally of clustering algorithms. We present a heterogeneous vehicular network architecture, which supports DSRC- and Device-to-Device-based communications for vehicle-to-vehicle to improve routing reliability. We prove that the optimal clustering problem is NP-hard. Therefore, we develop a heuristic algorithm, which by taking into consideration the stability degree of vehicles over the prediction horizon, finds a near-optimal solution. We propose a hybrid routing protocol based on our adaptive clustering scheme to achieve a high packet delivery ratio and low delay. Our hybrid routing protocol is composed of generic

Design of a lightweight authentication scheme for IEEE 802.11p vehicular networks

Roadside Units (RSUs), which enable the vehicles-to-infrastructure communication, are deployed along the roadside to handle the growing communication demands as the number of vehicles increases. How to optimally deploy the RSUs and efficiently use them to enhance the vehicular network performance are important problems in the RSU-aided opportunistic networks. In order to solving these problems, we need to understand fundamental laws and properties of the opportunistic contacts. Due to the prohibitive costs to collect enough realistic contact records, to the best of our knowledge, little experiment work has been conducted to study the communication contact patterns in RSU-aided opportunistic networks. In this work, we carry out an extensive experiment involving tens of thousands of operational taxis in Beijing city. Based on this newly collected Beijing trace and the existing Shanghai trace, we find some invariant characters for the communication contacts for large scale RSU-aided vehicular opportunistic networks. In terms of inter-contact time between the RSUs and vehicles, we find it obeys exponential distribution, while in terms of contact rate, it follows Poisson distribution. Our observations reveal fundamental patterns for large scale vehicular mobility, and further provide useful guidelines for the design of new routing protocols and their performance evaluation for RSU-aided vehicular opportunistic networks.