Collaborative content dissemination enables vehicles to directly access content from surrounding nodes through Vehicle-to-Everything (V2X) technologies, such as Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communication. This approach significantly alleviates the downlink traffic burden on cellular network base stations caused by repeated downloading of popular content while addressing security challenges in electric vehicle (EV) charging operations, such as payment fraud and data tampering. A key yet unresolved challenge in content dissemination and EV charging is incentivizing vehicles to participate in collaborative processes voluntarily. Existing incentive mechanisms mainly rely on centralized architectures, which are vulnerable to single-point attacks and trust issues in third-party platforms. To overcome these limitations, we propose the PCD-DB (Popular Content Dissemination using DAG-based Blockchain) scheme, which uses a Directed Acyclic Graph (DAG)-based blockchain to incentivize V2X collaboration for dual applications: improving content dissemination efficiency and ensuring secure EV charging transactions. Our novel framework establishes a decentralized incentive system where vehicles act as content propagators or charging service providers, depending on their service capabilities. We define the propagation and charging capabilities of vehicles and use contract theory to design hierarchical contracts tailored to heterogeneous vehicle roles. Numerical results show that our decentralized incentive mechanism significantly improves the efficiency and profitability of vehicle content dissemination while ensuring the security of electric vehicle charging transactions, outperforming existing benchmark methods.

Cooperative content dissemination allows vehicles to directly retrieve content from each other by vehicle-to-vehicle (V2V) communications. It can release the downlink traffic pressure caused by repetitive of popular content downloads. A critical but open issue is how to motivate vehicles to participate in content dissemination. Most of the existing incentive mechanisms are proposed under a centralized architecture that suffers from the single point attack and trustless third-platform. In this paper, we propose a decentralized incentive mechanism for cooperative content dissemination in vehicular networks. By introducing the Directed Acyclic Graph (DAG) based blockchain technology, a decentralized architecture is proposed, which can improve incentive efficiency and reliability by removing the third-platform. Next, using the contract theory, the vehicles are divided into different types according to their route feature, and a series of contracts are designed for different types of vehicles to provide suitable incentives, as well as maximize the content generators' profit. Simulation results demonstrate the effectiveness and efficiency of our solution.

The fifth-generation (5G) mobile communication systems support the millimeter-wave (mmWave) communications, which enable content dissemination for enhanced V2X (eV2X) services. However, the current content dissemination architectures face various problems, such as limited radio coverage of mmWave communications and differentiated Quality-of-Experience (QoE) requirements of users. To address these, we propose a regional-centralized content dissemination (RC-CD) scheme for eV2X services. The RC-CD can deal with the requests from distributed vehicles by the regional-centralized service architecture. By introducing vehicle-to-vehicle and vehicle-to-infrastructure mmWave communications, the content dissemination services are expanded to the areas that the mmWave base stations cannot cover. According to different QoE requirements, the requests of eV2X services are categorized into two groups: 1) elastic requests and 2) inelastic requests. Our algorithm considers the channel characteristics of mmWave and the different QoE requirements of requests to jointly optimize the waiting time of elastic requests and the failure ratio of inelastic requests. It also adopts an efficient heuristic approximate algorithm to solve the NP-completed optimization problem. The performance of our proposed scheme is evaluated by simulations in a realistic city layout. The results show that our scheme can provide an efficient architecture for eV2X content dissemination that supports different types of requests, provides a better QoE for the users, and achieves broader service coverage.

In Vehicular Ad Hoc Networks (VANETs), the unreliable wireless environment and highly dynamic topology make multi-content distribution inefficient due to the large amount of content requests from vehicles. This gives rise to the need for new content distribution schemes in VANETs. Current researches on content distribution for VANETs generally focus on the single type of content. In this paper, we consider both elastic (with no hard delay requirement) and inelastic (with a hard deadline) contents and propose a joint content distribution scheme in VANETs. We model the content distribution as an optimization problem which jointly minimizes the waiting delay of elastic requests and the failure ratio of inelastic requests. Then, we propose an efficient clonal selection-based approximate algorithm to solve the optimization problem. The performance of our scheme is evaluated by simulation using realistic vehicular traces. Simulation results show that our proposed scheme has better performance than previous solutions.

As one of the key services for non-safety applications in Vehicular Ad-hoc Networks (VANETs), the Popular Content Distribution (PCD) has become a hot issue in recent years. In popular content distribution, the On-Board Units (OBUs) passing the Area of Interest (AoI) receive popular content broadcast by the RoadSide Units (RSUs). However, due to the high speed of OBUs, limited bandwidth, and unstable wireless connections, only a portion of the popular content can be received by OBUs. To address this issue, in this paper, a cooperative V2V-aided transmission scheme based on a coalitional game (CVCG) is proposed. The scheme allows the OBUs to cooperate with their neighbors to provide the missing popular content. In addition, a coalition graph game algorithm is designed for optimizing the cooperative behaviors among OBUs. The performance of our CVCG scheme is evaluated by different metrics compared to other three content distribution schemes. The numerical results show that the proposed CVCG scheme could outperform the three schemes in terms of the number of iterations for 99 percent finished PCD, the average content completion percentage, and the number of completed OBUs.

In recent years, the rapid improvement of sensor and wireless communication technologies powerfully impels the development of advanced cooperative driving systems, generating the demands to form the Internet of Vehicles (IoV). With the assistance of cooperative communication among vehicles, the road safety can be greatly enhanced in the IoV. In this paper, we propose a cooperative driving scheme for vehicles at intersections in the IoV. First, the driver’s intention is modeled by the BP neural network trained with driving dataset. Then, the identified intention is used as the control matrix of the Kalman filter model, by which the vehicle trajectory can be predicted. Finally, by collecting the information of vehicles’ trajectories at the intersections, we develop a collision probability evaluation model to reflect the conflict level among vehicles at intersections. Through obtained collision probability, the driver or the autonomous control unit can determine the next step to avoid the possible collisions. Numerical results show that our proposed scheme has high accuracy in terms of driver’s intention identification, trajectory prediction and collision probability evaluation.

In VANETs, information exchange plays an important role to make vehicles aware to each other and provide references for safety or non-safety related applications. At intersections, vehicles are forced to maintain a lower mobility thereby have more time to exchange on-road or off-road context information. However, if an effective control scheme is not applied to this specific scenario, a packet congestion is more likely occurring especially when the vehicle density is high and channel load is heavy. In this paper, to solve the aforementioned problem, a congestion control scheme based on non-cooperative bargaining game is proposed. Numerical results show that our proposed Joint Power and Rate Adjustment congestion control scheme (JPRA) can greatly alleviate the possible packets collisions thus reducing the average experienced delay in queue and increasing the number of successfully delivered packets on the receiver side.