Vehicular Cloud Network Research Articles

Efficient message authentication scheme with forward and backward security in Vehicle Cloud Network towards sustainable smart city

The Vehicular Cloud Network (VCN) serves as a crucial component of Intelligent Transportation Systems (ITS), playing an instrumental role in the development of sustainable smart cities. It merges the benefits of both Vehicular Ad Hoc Networks (VANET) and cloud computing. However, VCN faces significant security challenges due to the complexity of communication, the dynamic nature of the environment, and the privacy concerns of data. To address the issues of message security and privacy preservation in VCN, this paper introduces an identity-based key-insulated ring signature (ID-KIRS) scheme for VCN message authentication. Our scheme integrates a secure key update function to address key exposure issues, providing both forward and backward security. The security analysis confirms that our scheme ensures message integrity, unconditional anonymity, and unforgeability. The performance evaluation clearly demonstrates our scheme is efficient, and applicable to vehicle congestion situations, especially car accident scenarios.

Fuzzy logic‐based trusted routing protocol using vehicular cloud networks for smart cities

AbstractDue to the characteristics of vehicular ad hoc networks, the increased mobility of nodes and the inconsistency of wireless communication connections pose significant challenges for routing. As a result, researchers find it to be a fascinating topic to study. Furthermore, since these networks are vulnerable to various assaults, providing an authentication method between the source and destination nodes is crucial. How to route in such networks more efficiently, taking into account node mobility characteristics and accompanying massive historical data, is still a matter of discussion. Fuzzy logic‐based Trusted Routing Protocol for vehicular cloud networks (FTRP) is proposed in this study that determines the secure path for data dissemination. Fuzzy Logic determines the node candidacy value and selects or rejects a path accordingly. The cloud assigns a confidence score to each vehicle based on the data it collects from nodes after each interaction. Our study identifies the secure path on the basis of trust along with factors such as speed, closeness to other nodes, signal strength and distance from the neighbouring nodes. Simulations of the novel protocol demonstrate that it can keep the packet delivery ratio high with little overhead and low delay. FTRP has significant implications for deploying Vehicular Cloud Networks using electric vehicle technologies in smart cities. The routing data is collected with the help of Internet of Technology (IOT) sensors. The information is transmitted between vehicles using IOT gateways.

SLA-Based Service Provisioning Optimization in Vehicular Cloud Networks Using Fuzzy Logic

SLA-Based Service Provisioning Optimization in Vehicular Cloud Networks Using Fuzzy Logic

Toward a Generic Vehicular Cloud Network Architecture: A Case of Virtual Vehicle as a Service

In recent years, cloud computing has gained more and more popularity. The motivation towards implementing cloud computing in vehicular networks is due to the availability of communication, storage, and computing resources represented by communication, vehicles, roadside units (RSUs), and central servers. These resources can be utilized and provided to vehicles, drivers on the road, travellers, and customers on the internet. Intelligent Transportation System (ITS) applications can utilize vehicular cloud computing to provide efficient real-time services, as well as to improve transportation safety, mobility, and comfort levels for drivers. In this paper, all possible vehicular cloud models are presented. Each vehicular cloud model offers different services. Integrating all vehicular cloud models into one integrated system will provide all services and serve internet users, passengers, and vehicles. Therefore, a generic vehicular cloud model is proposed. After that, a new service called Virtual Vehicle is proposed in vehicular cloud computing. The virtual vehicle is a virtual machine that migrates from one physical vehicle to another. It provides the same services as the physical vehicle according to the consumer's requirements.

TCaS‐VN: A novel V2V communication scheme to improve traffic control and safety in vehicular cloud networks

SummaryRoad accidents and traffic congestion are the unavoidable consequences of the growing number of vehicles on the road. Conventional management systems are not effective in mitigating these issues. However, a range of technologies, including sensors, processors, vehicle‐based resources, and mobile cloud computing, can help solve traffic and safety problems. Vehicular cloud networks, a cutting‐edge technology for the development of intelligent transportation systems, face significant challenges, such as ensuring reliable service providers that maintain stable connections between vehicles. Roadside units (RSUs) play a crucial role in these networks, but they come with several drawbacks, including high costs, imbalanced load distribution, and unreliable connections. To address these issues, we propose the Traffic Control and Safety in Vehicular Networks (TCaS‐VN) algorithm, a cloud‐based sharing services framework for vehicles that eliminates the need for RSUs. This approach offers several advantages, including a twofold improvement in the lifetime of clusters, the elimination of noncluster head nodes, a 54% reduction in overhead, a 58% reduction in service search time, and a success rate of over 95% in service provisioning.

Hilbert curves-based location privacy technique for vehicular cloud networks

Hilbert curves-based location privacy technique for vehicular cloud networks

A novel clustering and optimal resource scheduling in vehicular cloud networks using MKMA and the CM‐CSO algorithm

SummaryVarious opportunities aimed at the employment of delay‐sensitive applications in the vehicular environment are presented by the vehicular cloud (VC). Contrary to diverse wireless networks, VC networks possess exceptional features among others, namely, shorter transmission time along with a higher dynamic topology. Although integration with the cloud offers higher storage along with computation capabilities, it as well entails restricted resource availability. The restrictions on the number of resources serve as a challenge in servicing the applications with their necessary quality of service (QoS) guarantees as the number of service requests for applications keeps on augmenting with diverse circumstances. Thus, the need for an effective scheduling methodology arises to decide the sequence of servicing application requests and successful utilization of a broadcast medium, along with data transmission. To do efficient resource scheduling on VC networks, an optimization algorithm, namely, the crossover and mutation (CM)‐centered chicken swarm optimization (CSO) is proposed and implemented with the help of a publicly available dataset. Initially, the VC infrastructure is initialized and some vehicle information is extracted as features. Next, the Brownian motion‐centered bacteria foraging optimization (BM‐BFO) algorithm chooses the essential features. Centered on the chosen features, the vehicles are clustered using the modified K‐means algorithm. Next, as for the cloud server's virtual machines (VMs), the resource information is extracted. Lastly, the CM‐CSO algorithm carries out the optimal scheduling in the VC by means of the clustered features of vehicles and features of the VM. The proposed techniques' findings are scrutinized and analogized to the other prevailing methodologies to confirm that the proposed work performs effectively and gives optimal resource allocation (RA) to the VC.

Framework of Geofence Service using Dummy Location Privacy Preservation in Vehicular Cloud Network

With the increasing prevalence of different mobile apps, many applications require users to enable the location service on their devices. For example, the geofence service can be defined as establishing virtual geographical boundaries. Enabling this service triggers entering and exiting the boundary area and notifies the users and trusted third parties. The foremost concern of using geofence is the privacy of location coordinates shared among different applications. In this paper, a framework called ‘TIET-GEO’ is proposed that allows users to define the geofence boundary; in addition, it monitors Global Positioning System (GPS) devices in real-time when they enter/exit a specific area. The proposed framework also proposes a dummy privacy preservation algorithm to generate K-dummy locations around the real trajectories when the user requests the Point Of Interest (POI) from the Location-Based Services (LBS). This article aims to enhance the location privacy preservation in geofence service, by generating a k-dummy location around the user location based on the radius size of the geofence area. The proposed framework uses token keys authentication to authorize the users in the Vehicular Cloud Network (VCN) service by generating secret token keys authentication between the client and services. The results obtained show the effectiveness of the proposed framework was on parameters like flexibility and reliability of responses from different sources, such as smart IoT devices and datasets.

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.

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.

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.

SLA-based service provisioning approach in vehicular cloud network

SLA-based service provisioning approach in vehicular cloud network

Blockchain-Inspired Secure Computation Offloading in a Vehicular Cloud Network

With the emergence of computation-intensive vehicular applications, computation offloading based on mobile-edge computing (MEC) has become a promising paradigm in resource-constrained vehicular cloud networks (VCNs). However, when doing computation offloading in a VCN, malicious service providers can cause serious security concerns on the content offloading. To address that in this article, a blockchain-based secure computation offloading scheduling scheme is proposed. It embraces the blockchain-based trust management paradigm and smart contract-enabled deep reinforcement learning (DRL) algorithm. As for the trust management, the long-term reputation and short-term trust variability are jointly considered. Specifically, a novel three-valued subjective logic (3VSL) scheme is adopted to obtain a more comprehensive reputation, and the statistics of behavioral transitions can provide a short-term trust variability to timely capture the malicious behaviors. In addition, to securely update, validate, and store the trust information, we propose a hierarchical blockchain framework that comprises vehicular blockchain, roadside unit (RSU) blockchain, and cloud blockchain. Furthermore, a smart contract-enabled DRL algorithm is proposed to implement the secure and intelligent computation offloading scheduling in a VCN. Simulations are conducted to verify the effectiveness of the proposed scheme.

Cost-effective and mobility-aware cooperative resource allocation framework for vehicular service delivery in the vehicular cloud networks

The traditional cloud empowered vehicular networks cannot adequately meet the very low-latency prerequisites of real-time vehicular applications due to the absence of a suitable resource allocation...

Cost-effective and mobility-aware cooperative resource allocation framework for vehicular service delivery in the vehicular cloud networks

Cost-effective and mobility-aware cooperative resource allocation framework for vehicular service delivery in the vehicular cloud networks

Cost Optimization based Resource Allocation Scheme for Vehicular Cloud Networks

Cost Optimization based Resource Allocation Scheme for Vehicular Cloud Networks

An adaptive resource placement policy by optimizing live VM migration for ITS applications in vehicular cloud network

AbstractVehicular cloud computing (VCC) is a promising approach that uses cloud computing techniques in vehicular environment to execute smart applications. Vehicular environment is characterized by high mobility. This requires the services executed by a vehicular resource in a vehicular cloud to be migrated before it leaves a network. Migration is also required when a service‐requesting vehicle has to leave a network before its request is executed. Moreover, to balance the network load, virtual machine (VM) migration is desired as, at times, a single physical host may become overloaded. In this work, we propose an adaptive resource placement policy by optimizing live VM migration process in vehicular cloud network. The Pareto optimal mapping of migrating VMs to a physical host is carried out using a hybrid optimized algorithm, which is the combination of particle swarm optimization and genetic algorithm. The optimization is done by maximizing a fitness function that is developed by considering significant quality‐of‐service (QoS) parameters, such as network latency, migration delay, power consumption, and vehicular mobility. These QoS parameters are mathematically formulated in view of a vehicular network. The proposed algorithm reduces migration latency, transmission latency, and service delay. It also distributes the load among the available physical hosts within a cloud system, thus reducing the average wait time for each cloud user. Simulation results exhibit significant decrease in waiting time, service delay, and migration delay. It is also shown that the proposed algorithm reduces total power consumption of the system.

TOPVISOR: Two‐level controller‐based approach for service advertisement and discovery in vehicular cloud network

SummaryVehicular cloud is a kind of mobile cloud in which vehicles share their resources and provide services for each other. The first step in establishing a vehicular cloud network is the service advertisement and discovery. Due to the dynamic nature of vehicular cloud networks, services are not continuous and the service location may vary at any time depending on the vehicle location. Therefore, higher network traffic is generated to access the consistent and up‐to‐date information. In this paper, a two‐level hierarchical approach is proposed for service advertisement and discovery in vehicular cloud networks. To register the services' specification in this approach, the distributed directories in RSUs and central controllers are used. Moreover, a method is used to avoid extra update packets by localizing the updates. The simulation results show improvement in the packet delivery rate as well as a reduction in transmission bandwidth preventing the network congestion.

Securing vehicular cloud networks

<p>Vehicular Cloud Networks (VCN) is the network that ensures mobility and availability of resources allowing new services and applications like Network as a Service (NaaS), STorage as a Service (STaaS), Computation as a Service (CompaaS) and Cooperation as a Service (CaaS). In this paper, we propose a solution to secure the Vehicular Cloud Network (VCN). Our challenge in this work is to adapt the PKI architecture, which is mainly used in wired networks to be used in VCN. To propose a security solution for Vehicular Cloud Networks (VCN), our work is based on three steps; the first one is to make network architecture study, where we tried to highlight the main network components. The second step is to propose the security solution architecture. Finally, the last step is to program a test and validate the solution using a simulation.</p>

Low-latency vehicular edge: A vehicular infrastructure model for 5G

With 5G network services around the corner, vehicular cloud networks providing computation capabilities have taken precedence over traditional costly cloud solutions. However, with vehicular cloud computing, a variety of new challenges have grown. In this paper we propose an intra-vehicle resource sharing model to provide a range of cloud services such as on-demand entertainment and speech recognition for driver assistance. The proposed solution forms nearby low-latency Vehicular Service Clouds (VSC) on-the-fly as per the needs of vehicular users. Vehicles in parking lots or moving on the road collaborate and share their computation and storage resources to complete different vehicular service requests. We develop an incentive-based model that uses edge-based Road Side Units (RSU) to compose heterogeneous node resources and produce a usable resource that satisfies users’ requests with minimal delays. Through proof of concept simulations, we compare our solution against traditional cloud solutions to showcase the effectiveness of adopting our proposed framework.