Characteristics Of Vehicular Ad Hoc Networks Research Articles

Knowledge-based system and expectation-maximization to discovering causes of imperfect labels in vehicular networks clustering

This paper focuses on the development of a knowledge-based system for automatically diagnosing issues in Vehicular ad hoc networks (VANETs). VANETs enable communication between vehicles and infrastructure, enhancing road safety and efficiency through timely information exchange. The proposed system aims to efficiently maintain and ensure the continuity of network service by leveraging innovative pattern recognition methods tailored to VANETs. The automatic diagnosis problem in VANETs involves estimating the operating class of network components based on sensor observations. This entails associating sensor measurements with specific operating modes. By implementing condition-based preventive maintenance procedures, potential component failures can be detected early, mitigating network disruptions. Various approaches, such as expert systems, fault trees, network state models, and statistical learning through pattern recognition, can be employed to address this problem. This paper primarily focuses on the statistical learning approach, where a classification or regression function is learned from a set of examples to assign operation modes to new measurements. It discusses relevant metrics and preprocessing techniques to simplify the decision-making process. The diagnostic system's results are determined based on the formulation of the classification or regression problem. The learning base is constructed, and an appropriate classification method is selected to develop and validate the automatic diagnosis system. While non-parametric models like support vector machines are commonly used, this article emphasizes the significance of considering assumptions and leveraging additional information to enhance performance. It proposes a more specific formalization of the problem, integrating the unique characteristics of VANETs. The contributions of this article revolve around the theory of belief functions, a generative approach, and the utilization of parametric models defined using graphical models. Experimental studies conducted on artificial datasets have demonstrated the benefits of the semi-supervised approach within the context of VANET networks.

Digital Twin for Transportation Big Data: A Reinforcement Learning-Based Network Traffic Prediction Approach

Vehicular Ad-Hoc Networks (VANETs), as the crucial support of Intelligent Transportation Systems (ITS), have received great attention in recent years. With the rapid development of VANETs, various services have generated a great deal of data that can be used for transportation planning and safe driving. Especially, with the advent of Coronavirus Disease 2019 (COVID-19), the transportation system has been impacted, thus novel modes of transportation planning and intelligent applications are necessary. Digital twins can provide powerful support for artificial intelligence applications in Transportation Big Data (TBD). The features of VANETs are varying, which arises the main challenge of digital twins applying in TBD. Network traffic prediction, as part of digital twins, is useful for network management and security in VANETs, such as network planning and anomaly detection. This paper proposes a network traffic prediction algorithm aiming at time-varying traffic flows with a large number of fluctuations. This algorithm combines Deep Q-Learning (DQN) and Generative Adversarial Networks (GAN) for network traffic feature extraction. DQN is leveraged to carry out network traffic prediction, in which GAN is involved to represent Q-network. Meanwhile, the generative network can increase the number of samples to improve the prediction error. We evaluate the performance of our method by implementing it on three real network traffic data sets. Finally, we compare the two state-of-the-art competing methods with our method.

Environment-Aware Adaptive Reinforcement Learning-Based Routing for Vehicular Ad Hoc Networks.

With the rapid development of the intelligent transportation system (ITS), routing in vehicular ad hoc networks (VANETs) has become a popular research topic. The high mobility of vehicles in urban streets poses serious challenges to routing protocols and has a significant impact on network performance. Existing topology-based routing is not suitable for highly dynamic VANETs, thereby making location-based routing protocols the preferred choice due to their scalability. However, the working environment of VANETs is complex and interference-prone. In wireless-network communication, the channel contention introduced by the high density of vehicles, coupled with urban structures, significantly increases the difficulty of designing high-quality communication protocols. In this context, compared to topology-based routing protocols, location-based geographic routing is widely employed in VANETs due to its avoidance of the route construction and maintenance phases. Considering the characteristics of VANETs, this paper proposes a novel environment-aware adaptive reinforcement routing (EARR) protocol aimed at establishing reliable connections between source and destination nodes. The protocol adopts periodic beacons to perceive and explore the surrounding environment, thereby constructing a local topology. By applying reinforcement learning to the vehicle network's route selection, it adaptively adjusts the Q table through the perception of multiple metrics from beacons, including vehicle speed, available bandwidth, signal-reception strength, etc., thereby assisting the selection of relay vehicles and alleviating the challenges posed by the high dynamics, shadow fading, and limited bandwidth in VANETs. The combination of reinforcement learning and beacons accelerates the establishment of end-to-end routes, thereby guiding each vehicle to choose the optimal next hop and forming suboptimal routes throughout the entire communication process. The adaptive adjustment feature of the protocol enables it to address sudden link interruptions, thereby enhancing communication reliability. In experiments, the EARR protocol demonstrates significant improvements across various performance metrics compared to existing routing protocols. Throughout the simulation process, the EARR protocol maintains a consistently high packet-delivery rate and throughput compared to other protocols, as well as demonstrates stable performance across various scenarios. Finally, the proposed protocol demonstrates relatively consistent standardized latency and low overhead in all experiments.

Recent Topology-based Routing Approaches in VANETs: A Review

Due to increasing both safety and efficiency of the traffic, Vehicular Ad Hoc Network (VANET) is a promising technology of Intelligent Transport Systems (ITS). Unique characteristics of VANETs including high mobility and strict delay constraints, require new routing solutions specific to these networks to be proposed. As one of those solutions, topology-based routing approaches aim to find the shortest path by managing routing tables. In this paper, recent topology-based routing approaches for VANETs are investigated in detail. Proactive, reactive and hybrid solutions are compared with respect to their advantages, disadvantages, updating procedures and network sizes. This paper will shed light on future studies since it provides detailed information about the current status of the literature in topology-based routing approaches in VANETs.

An Efficient Mobile Gateway Selection and Discovery Based-Routing Protocol in Heterogeneous LTE-VANET Networks

Coupling cellular communication networks with vehicular ad hoc networks (VANET) can be a very interesting way out for providing Internet access to vehicles in the road. However, due to the several specific characteristics of VANETs, making an efficient multi-hop routing from vehicular sources to the Internet gateways through Long Term Evolution (LTE) technology is still challenging. In this paper, an Internet mobile gateway selection scheme is proposed to elect more potential vehicles to behave as gateways to Internet in VANETs. Therefore, the discovery and the selection of route to those mobiles gateways is carried out via an efficient multiple metrics-based relay selection mechanism. The objective is to select the more reliable route to the mobile gateways, by reducing the communication overhead and performing seamless handover. The proposed protocol is compared with one recent protocol based on packet delivery ratio, average end-to-end delay and overhead. The results show that the proposed protocol ameliorates significantly the network performance in the contrast of the other protocol.

Towards Delay Tolerant Networking for Connectivity Aware Routing Protocol for VANET-WSN Communications

Vehicular Ad Hoc Networks (VANETs) are increasingly playing a fundamental role in improving driving safety. However, VANETs in a sparse environment may add risk to driving safety. The probability of a low density of vehicles in a rural area at midnight is very high. Consequently, the packet will be lost due to the lack of other vehicles, and the arrival of the following vehicles in the accident area is unavoidable. To overcome this problem, VANET is integrated with Wireless Sensor Network (WSN). The most challenging features of VANETs are their high mobility. This high mobility causes sensor nodes to consume most of their energy during communication with other nodes, leading to frequent network disconnectivity. With the evolution of VANET and WSN, the Store/Carry-Forward (SCF) paradigm has emerged as an exciting research area in the Delay Tolerant Networks (DTNs) to solve network disconnectivity. This paper proposes the Energy-Mobility-Connectivity aware routing protocol (EMCR) for a hybrid network of VANET-WSN. A comprehensive performance analysis that considers realistic propagation models and real city scenario traffic is performed in NS3. The simulation results show that the SCF mechanism is essential in the EMCR protocol to maximize the delivery ratio and minimize energy consumption and overhead.

DARVAN: A fully decentralized anonymous and reliable routing for VANets

With the recent advances in the automobile industry and the emergence of smart self-driving vehicles, the increasing need for proper and optimal Vehicular Ad-hoc Network (VANet) protocols has drawn the attention of many researchers. Nevertheless, the VANet community has yet to agree on a unified and suitable set of protocols for such networks. One of the major concerns in these networks is security considerations, which are significant because of the specific characteristics of VANet. In this article, we aim to address the location privacy and reliability issues in VANet routing protocols. We propose DARVAN, a fully decentralized infrastructure that provides anonymous and reliable routing in VANets. By employing a distributed database and collective consensus, DARVAN minimizes the exposure of critical data, which is conventionally stored and processed in centralized units. DARVAN is deployed by modifying the I2P protocol, which aims to improve routing reliability and resilience to many adversary activities in VANets. Specifically, with DARVAN, we present an effective and efficient network-level mitigation for Sybil attacks in Vanets. Our extensive simulations on NS3 show that DARVAN performs well in terms of packet delivery ratio, overhead, delay, and reliability compared to the previous anonymous scheme proposed for VANet routing.

Comparative Analysis of Low and High Scalable VANET in terms of Receive Rate, Packets Received, MAC/PHY Overhead and Average Goodput

The modern advancements in mobile and wireless communications have made an tremendous change in human lifestyles. Mobile Ad-hoc Networks (MANETs) are self-organized and self-configured networks consisting of moving nodes that communicate through wireless communication systems. Vehicular Ad-hoc Network (VANET) is a special category of MANETs with some distinctive set of characteristics. Some common features of VANET are its use of multi-hop communications between mobile vehicles with limited bandwidth and self-organization of the moving vehicles. Also, VANET is differed from MANET by the feature of high mobility of nodes. One significant advantage of VANET over MANET is that the computing devices get continuous power from its vehicles. Scalability refers to a VANET's ability to accept a rising number of communicating vehicles without experiencing disruption or loss in data transfer or traffic loading, which increases administrative complexity and reduces network performance. Because of its difficult properties, designing a scalable and robust network is an open topic of research in VANET. When VANETs go from sparse to dense mode, or from high mobility to slow traffic conditions, several design methods fall short. The performance metrics Average Goodput, MAC/PHY overhead, packet received, and receive rate over four VANET routing protocols- Ad-hoc On Demand Vector (AODV), Destination Sequenced Distance Vector (DSDV), Dynamic Source Routing (DSR), and Optimized Link State Routing (OLSR) in a defined area. The results showed that DSR performed well in average goodput,MAC/PHY overhead, receive rate, and packets received in low and highly scalable scenarios.

A Black Widow Optimization-Based Neuro-Fuzzy Model for Designing an Efficient Cluster Routing Protocol in a VANET Environment

Vehicular ad hoc networks (VANETs) are the form of mobile ad hoc network that offers comfort and protection to road consumers. Accident prevention and traffic safety are improved by using VANET. One of the challenging tasks is developing an efficient routing protocol due to the VANET characteristics including rapid topology changes, frequent link disconnection, and self-organizations. Clustering is an important strategy for solving these issues in the mobile environment. In this study, we have proposed an evolutionary Black Widow Optimization (BWO) based Neuro-Fuzzy Optimization (EBW-NFO) algorithm for a cluster routing protocol that considers mobility constraints, mistrust value parameters, and Quality of Service (QoS) requirements. During communications, the connectivity and stability are increased and the EBW-NFO algorithm offers a stable and reliable clustering protocol. The experiments are conducted using an NS2 simulator and the performance is verified using different performance metrics

Clustering Review in Vehicular Ad hoc Networks: Algorithms, Comparisons, Challenges and Solutions

The Vehicular Ad-hoc Network (VANET) represents a new future for dynamic information dissemination between societies. VANET has a wide range of applications in a variety of aspects, including Intelligent Transportation Systems (ITS). VANET has some characteristics, like highly dynamic topology and intermittent connections. These characteristics lead to untrustworthy information transmission in VANET. Vehicle clustering is an efficient approach to improve the scalability of the network and connection reliability. The performance of the clustering is also affected by VANET characteristics. This article provides a comprehensive description of VANET clustering algorithms. The most notable clustering algorithms introduced between 1999 and 2021 are reviewed. A complete survey on clustering in VANETs is provided based upon the clustering process. The clustering process in most algorithms is explored in the aspects of CH selection metrics, cluster formation, and cluster maintenance. The clustering techniques based on some parameters like stability, convergence, overhead, and latency are compared. Some of the most common problems, as well as the approaches employed to solve them, are also discussed. Also, the performance parameters which evaluate the clustering approaches are summarized.

A Review on Integration of Vehicular Ad-Hoc Networks and Cloud Computing

The vehicular network is becoming a prominent area of research in the field of smart transportation systems. In such systems, smart vehicles are embedded with the onboard unit, which includes computing systems, communication devices, and storage equipment, and these vehicles are used to provide efficient traffic management and road safety. For many years, several solutions are addressed by many practitioners regarding different issues and challenges that arise in a vehicular network. One of the solutions is vehicular cloud computing (VCC). VCC is a promising technology that has created a great impact on the services and applications of vehicular ad-hoc networks (VANETs) by exploiting the vehicular resources effectively. In this paper, we present a survey on VCC, which integrates VANETs and cloud computing (CC). The basic overview and characteristics of VANETs are discussed. The architecture and several features of VCC are explored. We also discuss various privacy and security-related issues in VCC. Lastly, we focus on open issues, existing work, and future research directions.

A fog-assisted system to defend against Sybils in vehicular crowdsourcing

Technological advancements in vehicular transportation systems have led to the growth of novel paradigms, in which vehicles and infrastructures collaborate to infer high-level knowledge about phenomena of interest. Vehicular Social Network (VSN) is one such paradigm in which vehicular network entities are considered as part of an Online Social Network (OSN), paving the way for new services derived from social context. Although vehicular crowdsourcing has tremendous benefits, its deployment in real systems requires to solve important challenges including defense against Sybil attacks. This paper proposes a novel fog-assisted system that uses SybilDriver to minimize the presence of Sybil entities in VSN-based crowdsourcing applications. The proposed system exploits the characteristics of Vehicular Ad-hoc NETworks (VANETs) and OSNs to effectively recognize Sybils, and the adoption of fog computing helps reduce the overall network overhead by processing data closer to the vehicles. We perform detailed experiments on real-world publicly available datasets primarily to assess the effectiveness of SybilDriver against different Sybil attack strategies. Our experimental results show that SybilDriver detects Sybils with higher performance than state-of-the-art techniques under different settings. Furthermore, an evaluation of the fog architecture in terms of message complexity demonstrates low impact on the network overhead.

Comprehensive Review on Misbehavior Detection for Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) can increase road safety and comfort. It needs strong demand for security because the data sent in VANETs influence vehicles’ behavior. Existing studies have summarized VANET security, challenge, and attacks. This study aims to present a comprehensive overview of misbehavior detection in VANETs. First, VANET characteristics, security issues, and attacks are discussed. Then, the precise definition of misbehavior, detection mode, and detection objects are presented. Generic misbehavior detection is classified as data-centric and node-centric. In this study, to adapt to the VANETs scenario, we proposed a novel taxonomy of misbehavior detection, which considers the interaction between vehicles and which is refined by emphasizing the detection modes and participants. Finally, the remaining concerns, open issues, and prospective future research directions are discussed.

A Survey: Position based Non DTN and DTN Routing Protocol in VANET

An Intelligent Transportation System (ITS) is an advanced technology which aims to provide modern services such as smart parking, Emergency vehicle alert notification systems, automatic traffic management, direction of safe driving, accident prevention system and many. Vehicular ad-hoc networks (VANETs) play a significant role to implement an ITS system. In Vehicular Ad-hoc network, every vehicle and Road Side Units (RSU) take part in a communication to achieve the ITS services. Since nodes of VANET are different kind of vehicles with various speed, the formation of network will be more dynamic and scalability of network varies continuously. Due to dynamic characteristics of VANET, high density of traffic and more obstacles, routing is one the biggest challenge in urban area than rural area. In this paper we present an outline of VANET, taxonomy of routing, followed by a brief discussion of position based Non DTN and DTN routing protocol. Finally, we conclude the paper with comparison result of various position-based routing protocol.

Particle Swarm Optimization Video Streaming Service in Vehicular Ad-Hoc Networks

Owing to the increasing capabilities of mobile devices and the development of mobile communication techniques in vehicular ad hoc networks (VANETs), mobile multimedia services have focused on supporting high Quality of Service (QoS) and Quality of Experience (QoE) for the subscribers in video streaming services. In VANETs, high-quality video streaming services aim to provide safety, as well as various infotainment applications to the subscribers. Owing to the dynamic topology and frequent connectivity changes in moving vehicles, video streaming services require elastic and continuous updates of vehicle information to present interactive real-time views of nontrivial scenarios on roads. To achieve high QoS and QoE of video streaming services in VANETs, this paper proposes a novel protocol named PSOstreaming that is based on a particle swarm optimization (PSO) which is one one of the mainstream and nature-inspired algorithms for swarm intelligence (SI). PSOstreaming calculates the PSQ score, which is the scoring method of the node in the topology in terms of the data communication capability measurement to analyze and optimize topology information in real-road circumstances. In addition, PSOstreaming utilizes a 3D vector mobility prediction algorithm for the mobility prediction method for the vehicles to address the characteristics of VANETs. In the topology, PSOstreaming defines Global PSO members and Local PSO members to disseminate video packets for video-streaming services to the service requester by computational equations. Experimental results indicate that PSOstreaming achieves high-quality video streaming services with a flexible response to dynamic topology changes and a high frame delivery ratio in terms of QoS and QoE.

An Enhanced Hybrid Glowworm Swarm Optimization Algorithm for Traffic-Aware Vehicular Networks

A subclass of a Mobile Adhoc Network (MANET) is a Vehicular Adhoc Network (VANET). It consists of self-configuring moving vehicles which are called nodes. It is an inevitable ingredient of intelligent transportation systems. The vehicular network has some permanent devices called roadside units and moving devices called On Board Units (OBU). Every vehicle traveling on the network must possess the OBU. Safety and non-safety tidings are broadcasted in vehicular networks. Even vehicular network is derived from MANET and its characters are discriminated against the MANET. The various unique characteristics of VANETs are high mobility, changes in network topology, size of the network, long distance between the vehicles, frequently changing vehicle density, and limited time. Because of these special features, the traditional security and routing mechanisms are not suitable for VANETs. Also, the safety messages are modified or discarded by the attacker or any other node and it may lead to the loss of privacy, integrity, confidentiality, and authentication of the data. So to enhance the security of VANETs, it is very much essential to invent a secure communication protocol, to protect the infrastructure of the network and the confidentiality of the data. The simulation results reveal that the secure communication using certificate revocation approach, energy-efficient enhanced secure routing protocol, traffic-aware secure routing for VANETs using Hybrid Enhanced Glowworm Swarm Optimization (HEGSO), and trust model for secure communication in VANETs is ensuring the security in VANETs. When compared to peer existing routing protocols, the proposed scheme significantly reduces the packet failure ratio, response time, and throughput. When compared to ARIOR and I-AREOR, the proposed HEGSO technique diminished delays by 20% and 34%, respectively.

Beacon-Based Non-Delay Tolerant Routing Protocols for VANET: A Systematic Comparison

A Vehicular ad hoc network (VANET) is a sort of wireless ad hoc network which are used to provide communications between nodes. The frequent topology change is considered a unique feature of VANET nature due to the high movement of its participating vehicles. Thus, the design of a routing protocol that could cope with VANET characteristics is very challenging. Position-based routing protocols are the most suitable approaches for VANET. In this paper researcher broadly discussed Beacon-based Non-Delay Tolerant Geographical-based routing protocols for VANET. The main concern is to discuss the characteristics disadvantages of those protocols. Finally, several research directions relevant to the focus of this survey are identified that define preferred features of the appropriate routing protocol that can cope with VANET challenges.

An Efficient Routing Protocol for Vehicular Ad-Hoc Networks

Background: VANETs (Vehicular Ad-Hoc Networks) are the subclass of MANETs, which have recently emerged. Due to their swift changing topology and high mobility nature, it is challenging to design an efficient routing protocol for routing data amongst both moving vehicles and stationary units in VANETs. In addition, the performance of existing routing protocols is not effective due to the high mobility characteristics of VANETs. Methods: In this paper, we proposed a link reliabiliy routing strategy that makes use of Restricted Greedy Forwarding by considering neighborhood vehicle density and the least, and average velocity with its own neighboring vehicles for the selection of the next forwarder. Results: The proposed approach is based on the assumption that at every junction the policepatrolling car (i.e. PCR junction node), forwards the packet to a vehicle onto the correct road segment only. The link reliability is ensured by the mechanism of the selection of the next forwarder. Conclusion: The objective of this paper is to increase route reliability to provide increased throughput without significantly affecting end-to-end delay. The simulation results reveal that the proposed approach Reliable GPSR(R-GPSR) outperforms the existing GPSR and E-GyTAR approach.

Big data analytics with oppositional moth flame optimization based vehicular routing protocol for future smart cities

AbstractPresently, smart city is designed to enhance the quality of life in city, fulfil the safety of the people, safe travelling, etc. Besides, big data has attracted significant attention among researchers in different fields as a large amount of data is being produced with diverse day‐to‐day applications. Besides, Vehicular adhoc network (VANET) is a kind of mobile adhoc network (MANET) that considers the vehicles as the nodes in a network. Since the VANET generates large amount of data, big data analytics can be used to gain meaningful understanding for improving the traffic management process such as planning, engineering, and operations. This paper designs a Big Data Analytics with Oppositional Moth Flame Optimization based Vehicular Routing Protocol for Future Smart Cities. The presented model maps the features of VANET with the attributes of the big data. In addition, oppositional moth flame optimization based vehicular routing (OMFOVR) technique is developed for VANET over the Hadoop Map Reduce standalone distributed framework. For validating the effectual performance of the proposed OMFOVR technique, a series of experiments were performed and the results are compared with the conventional NetBeans IDE platform. The experimental values showcased the betterment of the OMFOVR technique on the selection of routes over the compared methods.

Mobility Management in Vehicular Adhoc Network based on RSA Algorithm

Vehicular Ad-hoc Network (VANET) is become very popular in academia as well as in industry. The important characteristics of VANET faces difficulties on network issues. Specifically the mobility management will helpful to provide a seamless connectivity and improve the Quality of service. So we present an overview of mobility management in VANET based on RSA algorithm. During vehicle to vehicle communication driver do not want to share his personal information like vehicle names, license, number plate, speed position, moving port routes and user information. To protect all the information and save from any external attacks such algorithm is effective. Devised work is also useful and helpful to find the cause of accident or   any liabilities. Recent work on mobility management is discussed in this paper. Proposed work includes an ID based crypto system for valid user. For this paper we are implementing RSA algorithm. In which data is encrypted and then the data is converted to cipher text and then decrypted with a private key. And the receiver will get original data.