A Reputation and Security Mechanism for Heterogeneous Vehicular Networks

This brief examines recent developments in the Heterogeneous Vehicular NETworks (HETVNETs), integrating cellular networks with Dedicated Short-Range Communication (DSRC) for meeting the communications requirements of the Intelligent Transport System (ITS)services. Along with a review of recent literature, a unified framework of the HetVNET is presented. The brief focuses on introducing efficient MAC mechanisms for vehicular communications, including channel access protocols, broadcast/multicast protocols, the location-based channel congestion control scheme and the content-based resource allocation scheme. The cooperative communication between vehicles is discussed. This brief concludes with a discussion on future research directions, and provides the readers with useful insights into the future designs in the HetVNETs, to motivate new ideas for performance improvements in vehicular networks.

Intelligent transportation systems (ITSs), which can fulfill people's increasing requirements on mobility, have arisen as a popular research area. In order to implement the ITSs, a large amount of data needs to be executed within requested time. Due to the remote locations, cloud centers are no longer sufficient in data off-loading. A heterogeneous vehicular network, which consists of three kinds of computation resources, i.e., a cloud center, an edge node, and multiple vehicles, is, therefore, constructed to solve the aforementioned issues. First, considering the heterogeneity of each computation resource, the delay bound can be derived based on the martingale theory. Especially, data off-loading to the cloud center or to the edge node is assisted by road side units (RSUs). The communication link from the source node to the cloud center or to the edge node is modeled as a two-hop one. By utilizing the min-plus algebra, the two-hop link can be abstracted and analyzed in an equivalent single system further. Then, given a requested delay time, the maximum off-loading capacity of each resource can be obtained from the derived delay bound. When the tasks are smaller than the network available off-loading capacity, an optimal task allocation problem can, therefore, be constructed to minimize the overall delay violation probability. The numerical results are presented to show the performance of the proposed task allocation scheme in the heterogeneous vehicular networks. In addition, it can be verified that the proposed optimal task allocation scheme performs better than the benchmarks in the literature.

Cluster stability-driven optimization for enhanced routing in heterogeneous vehicular networks

The supporting infrastructure and communications technologies for vehicular networking contexts are heterogeneous by nature. Large coverage access networks, such as 3G/4G, coexist with wireless local area networks and dedicated short-range communications. In such a scenario, we investigate the seamless provision of mobile Internet access and general IP services over the heterogeneous network, in particular for loosely coupling architectures. We propose a hybrid global mobility scheme that allows for the ongoing IP sessions to be transferred across dissimilar radio access networks that may belong to different administrative domains. In order to achieve the global mobility, our scheme combines host- and network-based mobility. The solution focuses on urban vehicular scenarios and enables seamless communications for in-vehicle networks, passengers with mobile devices, and users of public transportation commuting along the system. By means of analytical evaluations and simulations of realistic urban vehicular scenarios, we show that our hybrid scheme can achieve seamless IP communications for mobile Internet access over the heterogeneous vehicular network.

Internet of Vehicles (IoV) is an emerging concept that is believed to help realize the vision of intelligent transportation systems (ITSs). IoV has become an important research area of impactful applications in recent years due to the rapid advancements in vehicular technologies, high throughput satellite communication, the Internet of Things, and cyber-physical systems. IoV enables the integration of smart vehicles with the Internet and system components attributing to their environments, such as public infrastructures, sensors, computing nodes, pedestrians, and other vehicles. By allowing the development of a common information exchange platform between vehicles and heterogeneous vehicular networks, this integration aims to create a better environment and public space for the people as well as to enhance safety for all road users. Being a participatory data exchange and storage, the underlying information exchange platform of IoV needs to be secure, transparent, and immutable in order to achieve the intended objectives of ITS. In this connection, the adoption of blockchain as a system platform for supporting the information exchange needs of IoV has been explored. Due to their decentralized and immutable nature, IoV applications enabled by blockchain are believed to have a number of desirable properties, such as decentralization, security, transparency, immutability, and automation. In this article, we present a contemporary survey on the latest advancement in blockchain for IoV. Particularly, we highlight the different application scenarios of IoV after carefully reviewing the recent literature. We also investigate several key challenges where blockchain is applied in IoV. Furthermore, we present the future opportunities and explore further research directions of IoV as a key enabler of ITS.

Vertical handover is one of the key technologies that will enable the connected and autonomous vehicles deployment. The emergence of vehicular networks—V2V, V2I, V2X—communications has enabled new applications, such as cooperative intelligent transport systems (C-ITS), real-time applications. However, these networks are characterized by a high level of mobility and dynamic change in the topology, which generates scattered networks. To address this problem and ensure a high level of performance, a new concept denoted heterogeneous vehicular networks (HVN) emerged, which is a key concept of the internet of vehicles (IoV). It consists in a hybridization the vehicular network (IEEE 802.11p) and cellular networks (3G/LTE/4G). In this chapter, authors introduced this new concept of IOV and its architectures and communication layers. Then they explored the different existing data relaying mechanisms in order to propose a new classification of handover approaches. After that, they presented the support of handover mechanisms in LTE and finally highlighted some handover challenges and issues.

Many networks, such as P2P networks, MANETs, file sharing networks, and online auction networks rely on node cooperation. If a malicious node gains access to such a network it can easily launch attacks, such as spreading viruses or spam, or attacking known vulnerabilities. Reputation systems (RS) defend against malicious nodes by observing their past behavior in order to predict their future behavior. These RSs usually comprise of statistical models or equations that are designed by hand and only defend against specific patterns of attacks. In this paper, we propose a support vector machines (SVM) based RS that defends against many patterns of attacks. It can be retrained to detect new attack patterns as well. We discuss the challenges associated with building RSs and how our RS tackles each of them. We compare the performance of our RS with another RS found in the literature, called TrustGuard, and perform detailed evaluations against a variety of attacks. The results show that our RS significantly outperforms TrustGuard. Even when the proportion of malicious nodes in the network is large, our RS can discriminate between good and malicious nodes with high accuracy. In addition our scheme has very low bandwidth overheads.

Analysis and assessment of a knowledge based smart city architecture providing service APIs

Towards people-centric smart city development: Investigating the citizens’ preferences and perceptions about smart-city services in Taiwan

In Vehicular (Ad-hoc) Network (VANET), besides Vehicle-to-Vehicle communications (V2V), vehicles in VANET also exchange data with Road-Side-Units (RSUs) and Cellular Base Stations (Vehicle-to-Infrastructure communications (V2I)). With the introduction of Intelligent Transport Systems (ITS), VANETs possess a great potential in enabling surveillance services. The rapid development of wireless communication technologies recently results in empowering data exchange among vehicles, RSUs and Cellular Base Stations, improving various types of applications and services such as safety driving, route planning, traffic alert, and context-aware infotainment. However, the benefits offered by VANETs and ITS cannot be fully realized unless there is a mechanism to effectively defend against fake and erroneous information exchange from malicious or dysfunctional nodes to other vehicles and RSUs for their own purposes. In this regards, trust appears as one of the solutions for VANETs to establish secure connectivity and reliable services. The conceptual idea to tackle down this challenges is that only data from trusted vehicles is taken into account. Thus, the aim is to evaluate trust of a vehicle in exchanging high quality of information. This paper presents the trust concept, key characteristics, a trust evaluation model, and a prototype for trusted data exchange activities in VANETs.

The prime requirements of vertical handoff in the heterogeneous vehicular network are to ensure the quality of service requirements and to provide seamless connectivity to all mobile stations. In this research paper, Multiple Attribute Decision Making (MADM) classical methods are used like the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to make the handoff decisions process quickly and efficiently. Our method called ‘MADM-TOPSIS Scheme’ is the fusing of TOPSIS method with Fuzzy Logic Sets and Rules, in order to lessen the Blocking Probability. Performance results are thus compared with the classical fuzzy TOPSIS and with an approach of the base paper. Our work is able to determine properly that by reducing the blocking probability, the handoff probability will increase that will improve the network performance in the heterogeneous vehicular system. After differentiating to classical Fuzzy TOPSIS, our work scheme shows an upgrade of 0.10 and 20% with base paper.

With the rapid development of autonomous driving technologies, it becomes difficult to reconcile the conflict between ever-increasing demands for high process rate in the intelligent automotive tasks and resource-constrained on-board processors. Fortunately, vehicular edge computing (VEC) has been proposed to meet the pressing resource demands. Due to the delay-sensitive traits of automotive tasks, only a heterogeneous vehicular network with multiple access technologies may be able to handle these demanding challenges. In this article, we propose an intelligent task offloading framework in heterogeneous vehicular networks with three Vehicle-to-Everything (V2X) communication technologies, namely Dedicated Short Range Communication (DSRC), cellular-based V2X (C-V2X) communication, and millimeter wave (mmWave) communication. Based on stochastic network calculus, this article firstly derives the delay upper bounds of different offloading technologies with certain failure probabilities. Moreover, we propose a federated Q-learning method that optimally utilizes the available resources to minimize the communication/computing budgets and the offloading failure probabilities. Simulation results indicate that our proposed algorithm can significantly outperform the existing algorithms in terms of resource cost and offloading failure probability.

With the rapid development of autonomous driving and heterogeneous vehicular networks (HetVNets), vehicles can collect data and generate valuable information to obtain profits, thus forming a new vehicular self-media paradigm. However, with potential security risks, the current data trading schemes in the HetVNets lack the comprehensive consideration of the requirements of the participants including media data producers (MDPs), media data sellers (MDSs), and media data buyers (MDBs) to design a trading framework that integrates data caching services and data selling services. To this end, we propose an on-demand self-media data trading scheme in HetVNets. Specifically, based on blockchain and smart contracts, we first design an on-demand self-media trading architecture that jointly considers the data caching services and the data selling services to provide the participants with a secure transaction environment. In the data caching phase, by considering the value of media data generated by the MDPs and the sales capabilities of different MDSs, we model the requirements of the MDPs and the MDSs as utility functions and formulate the interactions between them as a Stackelberg game, where an iterative algorithm is designed for the MDPs and the MDSs to obtain their optimal strategies. In the data selling phase, we consider the diversified requirements of the MDBs and propose an iteration-based mechanism to help the MDSs dynamically determine the data selling strategies. Compared with the traditional schemes, the simulation results show that our scheme can obtain the optimal strategies for the MDPs and the MDSs and bring them the highest utilities.

The heterogeneous vehicular network (HetVNET), which consists of multiple radio access networks (RANs), is a promising paradigm to provide a variety of services on the road. However, with the diverse quality of experience (QoE) requirements for vehicles, how to choose the optimal network for the vehicles pose great challenges. In this paper, we investigate the network selection problem in a HetVNET, which includes LTE-vehicle-to-anything (LTE-V2X), dedicated short-range communications (DSRC), WiFi. The network selection problem is formulated as a stable matching between the vehicles and different RANs. A two-sided one-to-many matching algorithm is presented based on the preference lists of both vehicles and RANs. Numerical simulation results show that the proposed method can improve the total throughput of the system and reduce the total network switch time compared to some existing algorithms.

Quality of service aware multicasting in heterogeneous vehicular networks