Vehicular Cloud Research Articles

Optimized Processing Placement Over a Vehicular Cloud

Modern vehicles equipped with on-board units (OBU) are playing an essential role in the emerging smart city revolution. The vehicular processing resources, however, are not used to their full potential. The concept of vehicular clouds is proposed to exploit the underutilized vehicular resources to supplement cloud computing services to relieve the burden on centralized cloud data centers and improve quality of service. In this paper we introduce a vehicular cloud architecture supported by fixed edge computing nodes and a central cloud data center. A mixed integer linear programming (MILP) model is developed to optimize the allocation of the processing demands in the distributed architecture while minimizing the overall power consumption. The results show power savings as high as 84% compared to processing in the conventional cloud.Variations in the test cases to include processing demand and traffic demand splitting showed power saving of 71% and 16% respectively, even for large demand volumes. A heuristic algorithm with performance approaching that of the MILP model is developed to validate the MILP model and allocate processing demands in real time.

Edge Based Lightweight Authentication Architecture Using Deep Learning for Vehicular Networks

<p>When vehicles are connected to the Internet through vehicle-to-everything (V2X) systems, they are exposed to diverse attacks and threats through the network connections. Vehicle-hacking attacks in the road can significantly affect driver safety. However, it is difficult to detect hacking attacks because vehicles not only have high mobility and unreliable link conditions, but they also use broadcast-based wireless communication. To this end, V2X systems need a simple but a powerful authentication procedure on the road. Therefore, this paper proposes an edge based lightweight authentication architecture using a deep learning algorithm for road safety applications in vehicle networks. The proposed lightweight authentication architecture enables vehicles that are physically separated to form a vehicular cloud in which vehicle-to-vehicle communications can be secured. In addition, an edge-based cloud data center performs deep learning algorithms to detect car hacking attempts, and then delivers the detection results to a vehicular cloud. Extensive simulations demonstrate that the proposed authentication architecture significantly enhanced the security level. The proposed authentication architecture has 94.51 to 99.8% F1-score results depending on the number of vehicles in the intrusion detection system using control area network traffic.</p> <p> </p>

A Performance Modeling of Dynamic Vehicular Clouds: Job Completion Time of Concurrently Executed Tasks

A Performance Modeling of Dynamic Vehicular Clouds: Job Completion Time of Concurrently Executed Tasks

A Survey of Vehicular Network Systems for Road Traffic Management

In this survey, we analyze the proposals of vehicular communication systems in the context of road traffic management. Starting with the definition of communications between vehicles (V2V), vehicles-to-infrastructure (V2I) and vehicles-to-everything (V2X), we first focus on the requirements and current standards for the Intelligent Transport Systems (ITS), including the maximum communication delay, the communication range and the size of messages (in the case of V2I transmission). After that, we analyze the use cases in line with the implementation of intelligent traffic management and review the respective methods that support or directly manage traffic on roads. One of the primary objectives of this paper is to highlight the architectures of four classes of systems able to support vehicular traffic management and communication between vehicles and roadside infrastructure, namely: vehicular cloud computing (VCC), cloudlets, Mobile Edge Computing (MEC) and fog computing. In this context, we also present our classification of the methods for these four classes of architectures. In the end, we provide our opinion on problems and limitations concerning the deployment of mechanisms belonging to each considered architecture class.

Securing Real-Time Video Surveillance Data in Vehicular Cloud Computing: A Survey

Vehicular ad hoc networks (VANETs) have received a great amount of interest, especially in wireless communications technology. In VANETs, vehicles are equipped with various intelligent sensors that can collect real-time data from inside and from surrounding vehicles. These real-time data require powerful computation, processing, and storage. However, VANETs cannot manage these real-time data because of the limited storage capacity in on board unit (OBU). To address this limitation, a new concept is proposed in which a VANET is integrated with cloud computing to form vehicular cloud computing (VCC) technology. VCC can manage real-time services, such as real-time video surveillance data that are used for monitoring critical events on the road. These real-time video surveillance data include highly sensitive data that should be protected against intruders in the networks because any manipulation, alteration, or sniffing of data will affect a driver’s life by causing improper decision-making. The security and privacy of real-time video surveillance data are major challenges in VCC. Therefore, this study reviewed the importance of the security and privacy of real-time video data in VCC. First, we provide an overview of VANETs and their limitations. Second, we provide a state-of-the-art taxonomy for real-time video data in VCC. Then, the importance of real-time video surveillance data in both fifth generation (5G), and sixth generation (6G) networks is presented. Finally, the challenges and open issues of real-time video data in VCC are discussed.

PSEBVC: Provably Secure ECC and Biometric Based Authentication Framework Using Smartphone for Vehicular Cloud Environment

The Vehicular Cloud Environment (VCE) is a brand-new study field in cloud and vehicular network.It gives cars networking and sensor capabilities for V2I or V2V communication with roadside infrastructure. Cloud applications are frequently used in traffic control and road safety. A hybrid technical solution that utilises vehicle resources, cloud infrastructure, and Internet of Things (IoT) settings is needed for effective vehicular communication networking. VCE is a smart vehicular communication architecture that promotes system security, enhanced vehicle control, and self-driving cars. Due to the integration of unknown vehicles and infrastructure via the public network, security and privacy seem to be significant challenges with VCE. In this regard, we propose a PSEBVC, which is a provably secure elliptic curve cryptography (ECC) and biometric based authentication system for VCE employing smartphones. In the face of active and passive adversaries, the offered framework obtains the majority of security features and properties for secure communication. We also propose and prove a formal security model based on the random oracle concept. We also demonstrate the security analysis using the Scyther tool. In the same scenario, we evaluate the performance of our protocol against that of other frameworks. The proposed system, according to our findings, is both secure and efficient in terms of communication and processing overhead. The proposed architecture, according to our findings, provides all needed security criteria while also permitting effective communication.

A Comprehensive Review of Computing Paradigms, Enabling Computation Offloading and Task Execution in Vehicular Networks

Road safety, optimized traffic management, and passenger comfort have always been the primary goals of the vehicle networking research community. Advances in computer and communication technologies have made the dream of modern intelligent vehicles a reality through the use of smart sensors, cameras, networking devices, and storage capabilities. Autonomous operation of modern intelligent vehicles requires massive computations where tasks are outsourced. In recent years, various computing paradigms, e.g., mobile cloud computing (MCC), vehicular cloud computing (VCC), multi-access or mobile edge computing (MEC), vehicular edge computing (VEC), vehicular fog computing (VFC), and volunteer computing based VANET (VCBV), have been developed to move computational resources close to the user and handle the delay-sensitive applications of modern intelligent vehicles. Therefore, in this study, we provide a comprehensive overview of all computing paradigms related to vehicular networks. We also present the architectural details, similarities, differences, and key features of each computing paradigm. Finally, we conclude the study with open research challenges in vehicular networks along with future research directions.

Distributed integrity and non-repudiation scheme in the dynamic vehicular cloud environment

Distributed integrity and non-repudiation scheme in the dynamic vehicular cloud environment

Enhanced Obfuscation for Software Protection in Autonomous Vehicular Cloud Computing Platforms

Nowadays, sensors, communications connections, and more powerful computing capabilities are added to automobiles, making them more intelligent. The primary goal was to eliminate the need for human control, making them Autonomous Vehicles (AVs). Consequently, researchers thought to put all that newly added computational power to use for other endeavors. Hence, Autonomous Vehicular Cloud Computing (AVCC) models were introduced. Nevertheless, this goal is not an easy undertaking, the dynamic nature of autonomous vehicles introduces a critical challenge in the development of such a distributed computing platform. Furthermore, it presents far complicated issues as far as security and protection of services associated with this framework. In this paper, we center around securing programs running on AVCC. Here, we focus on timing side-channel attacks which aim to leak information about running code, which can be utilized to reverse engineer the program itself. We propose to mitigate these attacks via obfuscated compilation. In particular, we change the control flow of an input program at the compiler level, thereby changing the program’s apparent behavior and accompanying physical manifestations to hinder these attacks. We improve our previous ARM-based implementation to address its limitations and provide more comprehensive coverage for different programs. Our solution is software-based and generically portable - fitting different hardware platforms and numerous input program languages at the source level. Our findings prove a considerable improvement over our previous technique, which may provide more defense against timing side-channels.

An efficient authentication scheme for secured service provisioning in edge-enabled vehicular cloud networks towards sustainable smart cities

Vehicular networks are getting huge attention among the research community due to its tremendous potential to offer diversified applications and services to the drivers and passengers towards the realization of intelligent transportation system (ITS) for connected living and sustainable smart cities. Cloud computing (CC), which possesses large capacity in terms of computing and storage resource, may not be suitable for many vehicular applications like safety and emergency services due to high bandwidth requirement and large response time. Edge or fog computing can be a promising technology that can be integrated with vehicular networks to meet the requirements of less bandwidth usage and lower response time. Vehicular cloud network (VCN) extends cloud computing concepts among the vehicles in the vehicular networks to enable vehicles with excess computing, storage or bandwidth capacities to share the resources with other vehicles, who are willing to use that extra resource to fulfill their service requirements. Security poses a great challenge in a vehicular network due to high mobility, dynamic and frequent changes in topology and sudden variation in vehicle density in the roads. Privacy of the vehicular users must be ensured to encourage mass participation for making the system trustworthy. Both security and privacy are pre-requisites of a sustainable smart city. For secured service provisioning, before transmitting a message, connected vehicles must be authenticated. In this paper, we have proposed a system to authenticate vehicles for secured service provisioning in edge-enabled vehicular cloud networks. A novel technique has been developed to avoid redundant authentication to validate a vehicle successively across various RSUs (road side units). Extensive simulation works have been done and the outputs demonstrate efficacy of the proposed algorithm.

Data Partitioning and Scheduling Schemes for Federated Platoon-Based Vehicular Cloud

Data Partitioning and Scheduling Schemes for Federated Platoon-Based Vehicular Cloud

A SMDP Approach to Evaluate the Performance of a Vehicular Cloud Computing System with Prioritize Requests

In intelligent transportation systems, Vehicular Cloud Computing (VCC) is a new technology that can help ensure road security and transport efficiency. The study and evaluation of performances of a VCC is a topic of crucial interest in these environments. This paper presents a model of the computation resource allocation problem in VCC by considering heterogeneity and priority of service requests. We consider service requests from two classes, Primary service requests and Secondary service requests. We involve a Semi-Markov Decision Process (SMDP) to achieve the optimal policy that maximizes the performances of the VCC system taking into account the variability of resources, the income and the system cost. We utilize an iterative approach to achieve the optimal scheme that characterizes the action to be taken under each state. We validate our study by numerical results that show the effectiveness of the proposed SMDP-based scheme.

Framework of data privacy preservation and location obfuscation in vehicular cloud networks

SummaryThe leakage of sensitive data of users and global positioning system location trajectories from different cloud computation sources have increased in daily lives. This critical problem can influence users' lives because attackers try to misuse the leaked information. In this study, we addressed the critical problem pertaining to the privacy of personal identification information (PII) and location information over vehicular cloud networks (VCNs). The problem was addressed by proposing a data and location privacy (DLP) framework that preserves data privacy in terms of the anonymity of PII and provides location privacy for users' trajectories through the obfuscation technique. The proposed DLP framework contains five stages: registration with VCN server, processing of PII/data privacy block, segregation of obfuscation data, authentication, and provision of cryptographic security. The result analysis shows that the proposed mechanism is able to generate obfuscated trajectories and successfully recomputes the original trajectories at the server side.

Privacy preservation and secure data sharing scheme in fog based vehicular ad-hoc network

Due to the increase in vehicle numbers and various services, such as exchanging messages between vehicles under different traffic conditions and in an emergency, the vehicular cloud computing (VCC) has drawn significant attention. The current centralized system has the computation and safety requirements such as secure storage, authentication, access control, availability over alternative network connections, and a real-time summary of the data flow. The traditional method includes the transfer of data for processing from the edge node to a centralized server that reduces the available bandwidth and increases the latency across the network. Transmission of the vast amount of data from the edge devices to a central system increases the chances of getting a security breach that leads to compromised information and data loss. In this paper, we propose a Privacy Preservation and Secure Data Sharing Scheme in Fog Based Vehicular Ad-hoc Network by analyzing critical information and employing data confidentiality with the help of Hierarchical Attribute-Based Encryption (HABE) with an efficient key exchange. The proposed scheme also uses symmetric encryption and a Hash-based Message Authentication Code (HMAC) computation with the shared secret key to secure the message transmission between vehicles. It also provides fine-grained access control before outsourcing data to the cloud server to ensure privacy depends on ownership to reduce the number of data forwarded to the cloud server with a short period and decreases bandwidth requirements due to fast analytics at the edge. Assessment of the proposed scheme is done by finding the key generation computation cost on attribute authority, message broadcasting computation cost for vehicles, and message decryption computation cost for vehicles.

The Dynamic Movement of Disaster Management Systems Based on Vehicle Networks and Applied on the Healthcare System.

In order to save human life and assets, the emergency management system (DMS) requires roving rescue teams to respond promptly and effectively. Installation and restoration of appropriate communication infrastructure are important for reducing the effect of disasters and enabling and coordinating information flow among relief teams working in the region. This paper describes a data collection system based on vehicular cloud network services that incorporates the advantages of both architectures of vehicular ad hoc networks (VANETs) with the cloud to establish vehicular cloud networks (VCNs). Vehicles in the current plan perform tasks like monitoring the environment, gathering data, and transmitting data to the control center depending on their positions and instructions. To build a disaster management system, the proposed system uses hybrid wireless networking, which includes both a central system and ad hoc networks. The implementation results show that the suggested system is more dependable and efficient; even light density is improved in terms of reachability with few hops. Furthermore, as compared to the existing system, the suggested system has a lower end-to-end delay and a higher packet delivery ratio.

Environmental monitoring through Vehicular Ad Hoc Network: A productive application for smart cities

SummaryIndustrial growth, technological development, and increased human activities for comfort and luxurious life increase different environmental parameters like temperature, humidity, carbon monoxide, methane, and smoke. The value of these parameters are increasing steadily which has adverse effects on human life and human health and is also the cause of various disease like cancers and lung disease. It is now essential to monitor the environmental parameters of a region frequently. For the automatic continuous monitoring of environmental parameters of any location, this paper proposes to use vehicular ad hoc network (VANET), which is one of the promising subclasses of mobile ad hoc network (MANET). Automatic monitoring of environmental parameters of any location includes measurement of environmental parameters of a location, transmission of environmental parameters from the measured location to the observation center, and analysis of the parameters at the observation center. Two aspects are discussed for the transmission of parameters from the location of measurement to the observation center: first by vehicular communication and second by vehicular cloud. The analysis of the environmental parameters at the observation center is done using probabilistic neural network (PNN). Apart from this, different generic network parameters like end‐to‐end delay, number of hops, and network gaps for the proposed work are computed for the transmission of different environmental parameters and is compared with different VANET routing protocols like geographic source routing (GSR), anchor‐based street and traffic‐aware routing (A‐STAR), and peripheral node‐based geographic distance routing (P‐GEDIR). Vehicular motion is created using Simulation of Urban MObility (SUMO), and the network parameter values, like end‐to‐end delay and number of hops, are obtained using OMNET++. A testbed experiment is conducted for the classification of sensor data which is adoptable in practice.

A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles.

Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad.

Secure Estimation and Attack Isolation for Connected and Automated Driving in the Presence of Malicious Vehicles

Connected and Automated Vehicles (CAVs) rely on the correctness of position and other vehicle kinematics information to fulfill various driving tasks such as vehicle following, lane change, and collision avoidance. However, a malicious vehicle may send false sensor information to the other vehicles intentionally or unintentionally, which may cause traffic inconvenience or loss of human lives. Here, we take the advantage of vehicular cloud and increase the resilience of CAVs to malicious vehicles by assuming each vehicle shares its local sensor information with other vehicles to create information redundancy on the cloud side. We exploit this redundancy and propose a sensor fusion algorithm for the vehicular cloud, capable of providing robust state estimation of all vehicles under the condition that the number of malicious information is sufficiently small. Using the proposed estimator, we provide an algorithm for isolating malicious vehicles. We use numerical examples to illustrate the effectiveness of our methods.

FORESAM-FOG Paradigm-Based Resource Allocation Mechanism for Vehicular Clouds.

The Intelligent Transport Systems (ITS) has the objective quality of transportation improvement through transportation system monitoring and management and makes the trip more comfortable and safer for drivers and passengers. The mobile clouds can assist the ITS in handling the resource management problem. However, resource allocation management in an ITS is challenging due to vehicular network characteristics, such as high mobility and dynamic topology. With that in mind, we propose the FORESAM, a mechanism for resources management and allocation based on a set of FOGs which control vehicular cloud resources in the urban environment. The mechanism is based on a more accurate mathematical model (Multiple Attribute Decision), which aims to assist the allocation decision of resources set that meets the period requested service. The simulation results have shown that the proposed solution allows a higher number of services, reducing the number of locks of services with its accuracy. Furthermore, its resource allocation is more balanced the provided a smaller amount of discarded services.

SLA-based service provisioning approach in vehicular cloud network

SLA-based service provisioning approach in vehicular cloud network