Vehicular Cloud Network Research Articles

Agent Based Trust Establishment between Vehicle in Vehicular Cloud Networks

Agent Based Trust Establishment between Vehicle in Vehicular Cloud Networks

Intelligent VNFs Selection Based on Traffic Identification in Vehicular Cloud Networks

Internet of Vehicles (IoV) has become a significant research area due to its specific features and applications such as efficient traffic management, road safety, and entertainment. Vehicles are expected to carry relatively more communication systems, onboard computing facilities, storage, and increased sensing power. Vehicular Cloud Network (VCN) is a hybrid technology that has a remarkable impact on IoV by instantly using vehicular resources. Merging software-defined networking with VCN is valuable to vehicular networks. Network function virtualization can be deployed across the servers and vehicles within the VCN to provide customized agile services. Its deployment requires an appropriate management strategy that often manifests as the difficult online decision making tasks. This paper proposes an intelligent Virtualized Network Functions (VNFs) selection strategy. For satisfying the quality requirements of different vehicular services, this strategy is based on the results of traffic identification that utilizes deep neural network and Multi-Grained Cascade Forest to distinguish service behaviors. According to the order of VNFs, the vehicular network is divided into several layers where each arrived packet needs to be queued. The scheduler of each layer selects a layer to host the next VNF for the packets in the queue. Our experiments demonstrate that the proposed traffic identification method increases the precision by 7.7% and improves the real-time performance. Furthermore, the proposed model of VNFs selection reduces network congestion compared to traditional scheduling models.

Vehicular cloud networking: evolutionary game with reinforcement learning-based access approach

In this paper, we study the vehicular cloud access problem. We model it as an evolutionary game where the vehicles choose to cooperate or to access the conventional cloud through the LTE link. We focus on the centralised case, and we study the equilibrium of both homogeneous and heterogeneous players analytically. We propose an evolutionary game-based vehicular cloud access algorithm (EG-VCA). Moreover, we propose a distributed Q-learning-based vehicular cloud access algorithm (QL-VCA) that allows each vehicle to select the way to access independently to avoid the use of a centralised controller. The simulation results show that QL-VCA and EG-VCA algorithms present almost the same performances. Also, they offer better results compared to the cases of using and accessing only the CC or the VC. Numerical results are also established. They outline the convergence of the two algorithms to the same state of equilibrium.

Vehicular cloud networking: evolutionary game with reinforcement learning-based access approach

Vehicular cloud networking: evolutionary game with reinforcement learning-based access approach

Efficient Message Authentication Scheme with Conditional Privacy‐Preserving and Signature Aggregation for Vehicular Cloud Network

Vehicular cloud network (VCN) is deemed as the most promising platform for providing transportation safety, road optimization, and valued‐added application services. Because VCN is of distinguishing feature with super‐large scale and unstable communication, it is a challenging task to study efficient authentication scheme for VCN without losing security and conditional privacy‐preserving. To meet the challenge, a new efficient message authentication scheme is proposed in this paper. A batch message verification and signature aggregation are included in the proposed scheme to improve the authentication efficiency and decrease the communication cost. Compared with the similar conditional privacy‐preserving authentication schemes, the proposed scheme has superior performance in computation and communication cost. Simulation analysis further proves that the proposed scheme has better advantages in reducing the verification loss rate and message delay in the application of VCN.

Efficient and dynamic elliptic curve qu‐vanstone implicit certificates distribution scheme for vehicular cloud networks

In this paper, we introduce an efficient and dynamic elliptic curve qu‐vanstone implicit certificates distribution scheme for vehicular cloud networks. We are concerned about how to achieve efficiently and dynamically certificates distribution with a reduced cost. We design an efficient mechanism that reduces the communication cost and the computational overhead for more safety and robustness of intelligent transportation systems. Our proposal enables vehicles to request and obtain implicit certificates upon a secure request, which can be used for further signing exchanged messages. Due to the restricted nature of these certificates, a simple and efficient revocation method has been presented. It is literally based on selective revocation message delivery technique that reduces the number of messages needed for revocation phase and solves a bunch of drawbacks of existing solutions. An extensive analysis is performed to demonstrate how the proposed scheme can dynamically carry out an effective certificates distribution. We further discuss and evaluate simulation results to demonstrate the merits gained by the proposed protocol.

IPv6-Based Vehicular Cloud Networking

In a vehicular cloud network, content-centric approaches are usually employed to seek contents. In the content-centric approaches, data attributes are used for routing instead of a specific address such as an IP address; i.e, data attributes are broadcasted in a vehicular cloud network to seek target contents. This flooding inevitably increases the cost of contents acquisition. To reduce the cost of contents acquisition, we propose an IPv6-based vehicular cloud network where IP-based unicast instead of content-centric broadcast is used to achieve contents acquisition. In this work, a new address structure is proposed to build the relationship between an IP address and a kind of contents, and via this new address contents can be acquired from the nearest vehicular cloud member in the unicast way. This scheme is analyzed and evaluated, and the data show that this scheme effectively reduces the cost of contents acquisition.

Vehicular cloud networking: architecture and design principles

Over the past several decades, VANET has been a core networking technology to provide safety and comfort to drivers in vehicular environments. Emerging applications and services, however, require major changes to its underlying computing and networking models, which demand new network planning for VANET. This article especially examines how VANET evolves with two emerging paradigms: vehicular cloud computing and information-centric networking. VCC brings the mobile cloud model to vehicular networks and thus changes the way of network service provisioning, whereas ICN changes the notion of data routing and dissemination. We envision a new vehicular networking system, vehicular cloud networking, on top of them. This article scrutinizes its architecture and operations, and discusses its design principles.