Message Dissemination In Vehicular Networks Research Articles

Novel Emergency Message Dissemination in Vehicular Networks

The number of vehicles has increased proportionally over the last couple of times and this number is rising due to the increase in population extension and the number of vehicles that are manufactured every day. The high business viscosity leads to several problems, from which effectively propagating emergency messages is a major concern. VANETs (Vehicular Ad-hoc Networks), it is a vehicle networks of digital communication between cars, trucks, and also roadside units like antennas & buildings. In VANETs, significant challenges are faced, while disseminating the message across the network. The major challenges are the broadcast storm problem, hidden node problem, and packet collisions. We propose an Effective Emergency Message Dissemination Scheme (EEMDS) for urban VANETs. The scheme is grounded on our mobility metrics to escape communication outflow and to maintain the stability of the cluster structure. Every vehicle takes into account its direction and path loss factor for opting appropriate cluster head. Also, we introduce estimated link stability to choose a suitable dependent vehicle (an intermediary that communicates between multiple clusters) that reduces the number of retransmits and communication traffic in the network. Simulation results covey that NEMDS provides an acceptable end-to-end detention, information coverage, & packet delivery ratio compared to the eminent Emergency Messages dissemination schemes.

A Blockchain Based Federated Learning for Message Dissemination in Vehicular Networks

Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proof-of-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms other blockchain approaches in reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbor vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analyzed using Stackelberg game. The analysis of asymptotic complexity proves PoFL as the most scalable solution compared to other consensus algorithms in vehicular networks.

BTMPP: Balancing Trust Management and Privacy Preservation for Emergency Message Dissemination in Vehicular Networks

As a potential application field of the sixth-generation (6G) communication technology and a promising part of massive Internet of Things (IoT), vehicular networks have attracted considerable attention from both academia and industry in recent years, where the cooperative safety applications are a significant branch. It is widely acknowledged that 6G is able to provide high-throughput and low-latency wireless communication capability for vehicular networks, support massive interconnectivity in vehicular networks with diverse service requirements, and significantly improve the performance of vehicular networks. Both trust management and privacy preservation play significant roles in vehicular networks, and there exists a tradeoff between them. For providing a satisfactory solution to balance the trust management and privacy preservation in vehicular networks, we put forward a novel scheme named as BTMPP (which is able to provide both the precise trust management and strong conditional privacy preservation simultaneously) in this article by leveraging the famous bloom filter (BF)-based private set intersection (PSI) technology. Furthermore, the theoretical analysis for the correctness, strong conditional privacy preservation capability, strong robustness, precise trust management, and the other features is detailed, and a series of simulations are conducted. The results reveal that the proposed scheme significantly outperforms the existing schemes in several aspects.

Emergency Message Dissemination in Vehicular Networks: A Review

The number of vehicles on the roads has increased proportionally over the last couple of years and this number is likely to rise due to the increase in population growth and the number of vehicles that are manufacturing every day. This high traffic density leads to several problems, from which effectively disseminating the emergency messages is a major concern. Keeping in view the dynamic characteristics of VANETs, significant challenges are faced in disseminating the message across the network. The major challenges are the broadcast storm problem, hidden node problem and the packet collision. Many studies have been performed to devise an effective and reliable mechanism for disseminating emergency messages in a Vehicular ad-Hoc Network (VANET). Researchers have proposed different models to tackle various types of scenarios for emergency message dissemination. This paper not only reviews some recent contributions to emergency message dissemination in vehicular networks but also discusses various proposed methods based on Intelligent Transportation System (ITS), Internet of Things (IoT), Priority messaging, Clustering approach, Software Defined Network (SDN) and Fog Computing. We have also tried to explore the latest developments in emergency message dissemination using 5G networks.

A Topological Approach to Secure Message Dissemination in Vehicular Networks

Secure message dissemination is an important issue in vehicular networks, especially considering the vulnerability of vehicle-to-vehicle message dissemination to malicious attacks. Traditional security mechanisms, largely based on message encryption and key management, can only guarantee secure message exchanges between a known source and destination pairs. In vehicular networks, however, every vehicle may learn its surrounding environment and contributes as a source, while in the meantime, acting as a destination or a relay of information from other vehicles, and message exchanges often occur between “stranger” vehicles. This makes secure message dissemination against malicious tampering much more intricate. For secure message dissemination in vehicular networks against insider attackers, who may tamper the content of the disseminated messages, ensuring the consistency and integrity of the transmitted messages becomes a major concern which the traditional message encryption and key management-based approaches fall short to provide. However, it is challenging for a vehicle to distinguish which message is true when the messages received from multiple nearby vehicles are conflicting. In this paper, by incorporating the underlying network topology information, we propose an optimal decision algorithm that is able to maximize the chance of making a correct decision on the message content, assuming the prior knowledge of the percentage of malicious vehicles in the network. Furthermore, a novel heuristic decision algorithm is proposed that can make decisions without the aforementioned knowledge of the percentage of malicious vehicles. The simulations are conducted to compare the security performance achieved by our proposed decision algorithms with that achieved by the existing ones that do not consider or only partially consider the topological information to verify the effectiveness of the algorithms. Our results show that by incorporating the network topology information, the security performance can be much improved. This paper sheds light on the optimum algorithm design for secure message dissemination.

On the security of warning message dissemination in vehicular Ad hoc networks

Information security is an important issue in vehicular networks as the accuracy and integrity of information is a prerequisite to the satisfactory performance of virtually all vehicular network applications. We study the information security of a vehicular Ad hoc network whose message could be tampered by malicious vehicles. An analytical framework is developed to analyze the process of message dissemination in a vehicular network with malicious vehicles randomly distributed in the network. The probability that a destination vehicle at a fixed distance can receive the message correctly from the source vehicle is obtained. Simulations are conducted to validate the accuracy of the theoretical analysis. Our results demonstrate the impact of network topology and the distribution of malicious vehicles on the correct delivery of a message in vehicular Ad hoc networks, and provides insight on the design of security mechanisms to improve the security of message dissemination in vehicular networks.

Message Dissemination in Vehicular Networks on the Basis of Agent Technology

Vehicular Ad hoc Network (VANET) is a sub-family of Mobile Ad hoc Network (MANET). The principal goal of VANET is to provide communications between nearby nodes or between nodes and fixed infrastructure. Despite that VANET is considered as a subclass of MANET, it has for particularity the high mobility of vehicles producing the frequent changes of network topology that involve changing of road and varying node density of vehicles existing in this road. That‘s why, the most proposed clustering algorithms for MANET are unsuitable for VANET. Various searches have been recently published deal with clustering for VANETs, but most of them are focused on minimizing network overhead value, number of created clusters and had not considered the vehicles interests which defined as any related data used to differentiate vehicle from another. In this paper, we propose a novel clustering algorithm based on agent technology to improve routing in VANET.

Optimal RSUs placement with delay bounded message dissemination in vehicular networks

In order to transfer emergency messages from the accident site to the control center as soon as possible, the Roadside Units (RSUs) act as the most important roles in vehicular ad hoc networks (VANETs). However, we always hope to deploy the minimum number of RSUs because of the low market penetration of VANET-enabled vehicles and the deployment cost of RSUs. This paper presents a transmission delay analysis in urban areas with IID vehicles, and then reveal the relationship between the transmission time and message dissemination distance. According to the analysis, the optimal RSUs deployment problem is formulated. We propose three heuristic greedy strategies as code methods of genetic algorithms to solve the optimal RSUs placement problem with delay bound. Simulation results show that the solutions are efficient and the time complexity is lower than those existing algorithms.

A graph structure approach to improving message dissemination in vehicular networks

Efficient message dissemination in vehicular ad-hoc networks (VANETs) is crucial for supporting communication among vehicles and also between users and the Internet, with minimal delay and overhead but maximum reachability. To improve the message dissemination in these networks, we show the need to study the graph-theoretic properties of VANETs, since they neither follow the small-world nor the scale-free network characteristics often found in large self-organized networks. We consider three fundamental properties: connectivity, node degree, and clustering coefficient. For each property, we develop and validate analytical models for both the urban and highway scenarios, building an extensive graph structure perspective on VANETs. With this, we see how connectivity changes with network density, that VANETs exhibit truncated Gaussian node degree distributions, and that network clustering coefficients do not depend on the network’s size or density. We then show how these results can be used to generate individual behavior favorable to the whole network using local information. The usefulness of this new approach is demonstrated by proposing new mechanisms to enhance the urban vehicular broadcasting protocol UV-CAST. Our results show that these new mechanisms lead to excellent performance while reducing the overhead in the UV-CAST protocol.

Distributed Algorithm for Constructing Efficient Tree Topology for Message Dissemination in Vehicular Networks

Vehicular ad hoc network is an ad hoc network constituted among moving vehicles that have wireless dedicated short range communication (DSRC) devices in order to provide ubiquitous connectivity even if the road-side infrastructure is unavailable. Message dissemination in vehicular ad hoc networks is necessary for exchanging information about prevailing traffic information, so that the vehicles can take alternate routes to avoid traffic jam. A major challenge in broadcast protocols is that they result in flooding of messages that reduce the speed of dissemination due to collision. Dissemination of messages using tree topology reduces the number of rebroadcasts. Dynamicity Aware Graph Relabeling System model provides a framework to construct spanning tree in mobile wireless network. In this paper, we propose a new distributed algorithm for constructing an arbitrary spanning tree based on Dynamicity Aware Graph Relabeling System model, which develops a maximum leaf spanning tree in order to reduce the number of rebroadcasts and dissemination time. Our simulation results prove that the number of vehicles rebroadcasting the message is curtailed to 15% and the dissemination time required to achieve 100% reachability is curtailed by 10% under average vehicle density.

Analysis of Message Dissemination in Vehicular Networks

Safety-critical applications form the main motivation for intelligent transportation systems (ITSs). Studying the major concerns in such applications, i.e., delay and reliability, through mathematical analysis is extremely beneficial because it enables us to design optimized schemes. Such analysis is, however, challenging due to the dynamics of such a network. In this paper, we present a mathematical model to study delay and reliability of emergency message dissemination in vehicular networks. First, a basic model is presented using simplified assumptions about the channel. Then, we enhance the model using Rician distribution as a realistic fading model for vehicular environment. We make some interesting observations from the presented model. First, the end-to-end reliability has a fairly fast transition over time, which we formally prove in this observation. The second observation from the analytical model confirms the fact that using the vehicle density on the road is a good metric for setting the right forwarding probability in vehicles. We exploit this conclusion and propose a completely distributed forwarding strategy. Simulation studies indicate that our model does capture the delay characteristics of vehicular networks. It also affirms the effectiveness of our warning dissemination scheme in terms of delay and single-hop reliability in comparison with other well-known routing methods. We believe that this is a promising step toward accurate characterization of communication delay and reliability in vehicular networks.

Seeing is Believing—Enhancing Message Dissemination in Vehicular Networks Through Visual Cues

One of the stumbling blocks for implementation of Vehicular Ad Hoc Networks is the penetration rate: the percentage of vehicles that have the communication equipment installed. As the equipment deployment is unlikely to happen instantaneously, it is important to explore the performance gains achievable at low penetration rates. This especially pertains to safety applications, which are expected to provide life-saving information to all drivers on the road within a given region. We propose a technique that can be employed by safety applications to address the low penetration issue. By using visual cues on the equipped vehicles, such as specific patterns of hazard warning lights, we show that for all but the lowest vehicle densities, a radio penetration rate of 30% is sufficient to inform more than 95% of drivers in the region of interest in a timely manner.