Vehicular Social Networks Research Articles

Proximate Sharing of Downloaded Geo Data Using the Vehicular Social Network (VSN) Technique

This work proposed a clustering scheme for Point Of Interests’ (POIs’) geo data sharing in Vehicular Social Network (VSN). In the proposed scheme, some vehicles can form a cluster to downloaded POIs’ geo data when they are approaching to a new set of POIs. One vehicle is chosen as the cluster head to download POIs’ geo data using its cellular network and shares the downloaded POIs’ geo data to its cluster members using IEEE 802.11p network. This work (1) uses GPS to get vehicles’ locations to calculate the timing of triggering the clustering process, and (2) proposes a clustering method to organize a group of vehicles that are proximate with each other for a while during their touring to become a cluster. The simulation results show that the proposed scheme can have higher available distance and higher successful ratio of the complete sharing of downloaded POIs’ geo data.

Capturing Drivers’ Lane Changing Behaviors on Operational Level by Data Driven Methods

With the development of autonomous vehicles, advanced driver-assistance systems, and vehicular social networks, the requirement for vehicle trajectory prediction in lane changing is higher. Here, we propose a neural-network-based operational level lane-changing model using data-driven methods. First, we determine the inputs of the lane-changing model by analyzing the influence factors of the lane-changing behavioral model under the framework of the social force theory. The main influencing factors include the temporal destination, the historical trajectories of the lane-changing vehicle, and the relative distance between the surrounding vehicles in our lane-changing model. Our lane-changing model is built by deep neural networks (DNNs). Then, we determine the suitable network structure and other parameters by empirical data for the DNN. Finally, tests on empirical lane-changing trajectory data sets show that the operational level lane-changing model built by DNN is promising.

Segmented Bloom Filter Based Missing Tag Detection for Large-Scale RFID Systems With Unknown Tags

Radio frequency identification (RFID) is one of the key technologies of the Internet of Things, which has been widely applied to many scenarios, such as tracking, warehouse monitoring, and vehicular social network. In such applications, some of the objects are attached with low-cost tags, which need to be monitored carefully. Hence, the object monitoring can be achieved by missing tag detection in the RFID system. However, unknown tags, whose IDs are not known by the reader in prior, may exist in the system to interfere the missing tag detection and reduce the time efficiency. In this paper, we propose a segmented bloom filter-based missing tag detection scheme called SBFMD, which consists of two phases, i.e., deactivation phase and detection phase. The idea behind the proposed SBFMD scheme is to eliminate the useless slots away from the bloom filter-based frame to improve the detection efficiency. We theoretically optimize the parameters of the proposed SBFMD scheme to maximize the efficiency with a required reliability. Extensive simulations are conducted to evaluate the performance of the proposed SBFMD scheme, the results of which validate its effectiveness.

Using Mobile Nodes to Control Rumors in Big Data Based on a New Rumor Propagation Model in Vehicular Social Networks

Vehicle data, which may have some errors, provide a source for big data analysis. Car owners sometimes publish false information to protect their privacy or interests. The spread of these false messages will contribute to potential loss as rumors. Recently, the emergence of the vehicular social network has further accelerated the spread of rumors and anti-rumors. Researchers have proposed a number of methods to reduce the loss caused by rumors. However, these methods do not account for the fact that it takes some time for users to reply to the message after receiving the rumors. Each user responds differently to rumors, but previous methods do use fixed conversion rates in different states. To overcome these difficulties, individuals are classified as susceptible, trustful, contagious, immune or recoverable (STCIR). We propose a novel STCIR model to study the dynamic propagation of rumors. Each user is assigned a time threshold attribute to indicate the time delay of the user's response. In some cases, a user may receive a rumor repeatedly in the course of the time threshold. Furthermore, we introduce vehicular nodes as authorities that produce correct information to curb rumors through user forwarding, and the anti-rumors starting from users are regarded as a rumor cascade. The experimental results reveal that vehicular nodes can reduce the scale and number of rumors. Vehicular nodes emerge early and move fast, and by moving to a greater degree, these nodes can increase the efficiency of mitigating rumors.

Implicit aggressive driving detection in social VANET

Human errors are the main reason for traffic accidents. Detection of aggressive driving, e.g. speeding and driving with smaller safety distance than recommended, is currently in the domain of law enforcement services. We propose a novel approach for aggressive driving detection using received signal strength indicator value measurement in vehicular ad hoc networks. We present an introduction to vehicular social networks, cluster formation and a short description of our method. Proposal is critically discussed in terms of implementation and privacy issues, and is followed by guidelines for future work in that field.

XPMFS: A New NVM File System for Vehicle Big Data

How to improve the I/O speed of storage systems is crucial for the ability of vehicle big data to meet the demand of vehicular social networks. Non-volatile memory (NVM) is an effective method for improving the performance of storage systems. Meanwhile, metadata management efficiency has a significant impact on the I/O performance of storage systems. But the current metadata management strategy is not efficient and will decrease the endurance of NVM devices. We design a new file system with a distributed metadata management strategy for hybrid NVM consisting of NVDIMMs and PCIe NVM devices. Based upon the intrinsic characteristics of two types of NVM devices and different attributes in the metadata, the attributes are divided, reorganized, and distributed between the two types of NVM devices based on the access frequency. The basic attributes with high access frequency are stored in NVDIMMs and managed by the CPU using a hierarchical algorithm to ensure the efficiency of management. The extended attributes with low access frequency are converted to multiple key-value pairs to improve the scalability of management and are stored in the PCIe NVM devices. Then, the embedded processor in the PCIe NVM devices is used to manage these extended attributes in the form of key-value pairs. This can reduce the transfer between the CPU and the PCIe NVM devices and decrease the write amplification of the PCIe NVM devices as well as improve the efficiency of metadata management. Thus, the metadata management tasks can be distributed between the CPU and the embedded processor in the PCIe NVM devices to reduce the time overhead of metadata management. Finally, a prototype named XPMFS is implemented based on PMFS and PMBD. Fio and Filebench are used to test its performance against PMFS and Ext4-DAX on PMBD. For Ext4-DAX on PMBD, the results demonstrate that the XMPFS can reduce the write and read time overhead by 52% and 49%, respectively, improving the I/O performance by 1.5 times under real workloads. The I/O performance of XPMFS is only slightly inferior to that of PMFS, but it avoids the storage capacity limitation of PMFS and aims for hybrid NVM.

A cross layer protocol for traffic management in Social Internet of Vehicles

One of the important members of Internet of Things (IoT); transportation vehicles are utilizing sudden advancements of communication technology. Now days, to make the Social IoT (SIoT) a reality there are many on-going world-wide research initiatives and standardization efforts. Internet of Vehicles (IoV) is an extension to the concept of SIoT that proposes Social Internet of Vehicles (SIoV). SIoV is an example of SIoT, where Smart vehicles are the objects of SIoT that builds social relationship and interchanges information to enhance the driving knowledge and gives various services to the drivers. In this paper, the proposed Vehicular Social Networks based on the VIoT consist of a large number of sensors that transmit data wirelessly. However, the very high heterogeneity in hardware capabilities of things and QoS requirements for different applications limits the performance of classical layered protocol solutions and the existing cross-layer solutions for wireless sensor networks. The results show that the proposed VSNP (Vehicular Social Network Protocol) for VIoT based on WSN solution can achieve a global communication optimum and outperforms existing layered solutions. The novel cross-layer module is a primary step towards providing efficient traffic management and reliable vehicle to vehicle communication in the SIoT. We have proposed an algorithm to control traffic congestion and road safety for VIoT.

Grouping vehicles in Vehicular Social Networks

As vehicles have become intelligent objects, creating social friendships among them is justifiable. Internet of Vehicles (IoVs) and Vehicular Ad-hoc NETworks (VANETs) are associated terms that are recently highlighted to improve the transportation systems. Intelligent vehicles that can communicate with each other are the main component of vehicular networks (VNs). Indeed, they have resources for that intelligence: CPU, transceiver, sensors and memory. On the other side, social networks (SNs) are also brought to light to mainly study the human relationships. In this context, gathering these vehicles in social groups is reasonable to share their information by bridging VN and SN in a multidisciplinary research direction called vehicular social networks (VSNs).This paper will present a model to group vehicles in two types of social groups. Casual groups and permanent or formal groups will be discussed to increase social ties among vehicles that have the same interests. The results will be analyzed to clarify the most important factors that affect such these relationships.

Social acquaintance based routing in Vehicular Social Networks

The concept of Internet of Things (IoT) provides us the opportunity to interconnect different objects with the communication and processing capabilities for a diverse range of applications. Recently, Vehicular Social Networks (VSNs) have been introduced through the combination of relevant concepts from two primary disciplines, i.e., social networks and Vehicular Ad hoc Networks (VANETs). Inspired from the social acquaintance in our daily life, we present a Social Acquaintance based Routing Protocol (SARP) for VSNs, which collectively consider three social feature metrics to make a forwarding decision. Proposed protocol aims to reduce End-to-End delay and improve packet delivery ratio in VSNs. Additionally, SARP overcomes the shortcoming of topology based routing and optimum local situation of geographically based routing protocols by considering the global and local community acquaintance of nodes. We performed extensive simulations under constant node density with different mobility speed and constant speed with varying node density to study the effect of node mobility speed and density on end-to-end delay and packet delivery ratio. The simulation results show that SARP outperforms GPSR by 22% and 26% in terms of end-to-end delay and packet delivery ratio respectively. Also, SARP outperforms AOVD in terms of end-to-end delay.

Vehicular Social Networks: Enabling Smart Mobility

Vehicular transportation is an essential part of modern cities. However, the ever increasing number of road accidents, traffic congestion, and other such issues become obstacles for the realization of smart cities. As the integration of the Internet of Vehicles and social networks, vehicular social networks (VSNs) are promising to solve the above-mentioned problems by enabling smart mobility in modern cities, which are likely to pave the way for sustainable development by promoting transportation efficiency. In this article, the definition of and a brief introduction to VSNs are presented first. Existing supporting communication technologies are then summarized. Furthermore, we introduce an application scenario on trajectory data-analysis-based traffic anomaly detection for VSNs. Finally, several research challenges and open issues are highlighted and discussed.

A Cloud-Based Trust Management Framework for Vehicular Social Networks

The mobile industry’s evolution from 4G to 5G will lead to a deep progress on mobile applications that are widely used in some new environments, such as vehicular social networks (VSNs). In VSNs, which are considered the first automobile social networks, vehicular communication can facilitate large-scale data sharing between drivers and their neighbours. However, malicious users of VSNs can also disseminate false information over the network. Traditional public key infrastructure (PKI) cannot recognize these malicious users, as they all have authorized identities. Thus, a trust management mechanism is introduced to secure vehicular social data. This paper demonstrates a high-level trust management model and its deployment scheme based on a vehicular cloud system. We propose a layered trust management mechanism that benefits from efficient use of physical resources (e.g., computing, storage, communication cost) and explore its deployment in a VSN scenario based on a three-layer cloud computing architecture. Moreover, performance modeling of the proposed trust management scheme is conducted through a novel formal compositional approach – Performance Evaluation Process Algebra (PEPA). PEPA has superior features in compositionality and parsimony, which means that it can efficiently model systems with layered architectures and complex behaviours. PEPA also supports various numerical analyses through calculating its underlying continuous time Markov chains (CTMCs) directly or solving a set of approximated ordinary differential equations (ODEs). According to analysis outcomes, we analyzed several key performance properties of the scheme and related capacity issues in deployment. The findings also reveal an efficient investigation approach for evaluating the performances of trust models.

On Selecting Vehicles as Recommenders for Vehicular Social Networks

Vehicular social networks, as one type of new future networks, integrate mobile wireless communications and social networks together, and they have attracted a plenty of interest from researchers. This paper argues that vehicular social networks joined with cloud and fog computing platforms can serve as recommenders and play a significant role in social lives. A new application for recommender systems that selects vehicles as recommenders is proposed to support marketers in improving marketing effectiveness. Then, we propose three algorithms to enhance the marketers’ marketing effectiveness based on different evaluation standards. The first algorithm selects those vehicles that can obtain maximum benefits for the marketers, in which the vehicles are selected based on passing regions with more benefits. However, this selection method may lose some potential markets because of region limitations. The second algorithm selects those vehicles that can reach the maximum coverage ratio in the city and bring the marketers more marketing effectiveness in the future, although the current benefits are not the best. The third algorithm combines the two prior algorithms, finding a tradeoff between coverage and benefits. We finally evaluate the effectiveness of the proposed algorithm with real-world data to show the effectiveness and efficiency of the “On Selecting Vehicles as Recommenders for Vehicular Social Networks” scheme: for the scheme based on the benefit factor, the performance criteria of the benefit ratio can be improved by 21% over the existing selection methods; for the scheme based on the coverage factor, the performance criteria of the coverage ratio can be improved by 13% over the existing selection methods; and for the third selection algorithm based on the two factors, the performance criteria of the benefit ratio and the metric $\mathcal {F}_{i}$ can be improved by 18.9% and 13.7%, respectively.

Privacy-Preserving Schemes for Ad Hoc Social Networks: A Survey

We review the state of the art of privacy-preserving schemes for ad hoc social networks including mobile social networks (MSNs) and vehicular social networks (VSNs). Specifically, we select and examine in-detail 33 privacy-preserving schemes developed for or applied in the context of ad hoc social networks. Based on novel schemes published between 2008 and 2016, we survey privacy preservation models including location privacy, identity privacy, anonymity, traceability, interest privacy, backward privacy, and content oriented privacy. Recent significant attacks of leaking privacy, countermeasures, and game theoretic approaches in VSNs and MSNs are summarized in the form of tables. In addition, an overview of recommendations for further research is provided. With this survey, readers can acquire a thorough understanding of research trends in privacy-preserving schemes for ad hoc social networks.

D2D-based content delivery with parked vehicles in vehicular social networks

With the rapid advances in vehicular technologies and social multimedia applications, VSNs have emerged and gained significant attention from both industry and academia. However, due to the low communication ability between vehicles, heavy network traffic load, and limited storage capacity, VSNs face the challenge to improve the performance of content delivery to provide a pleasant and safe driving experience. Therefore, in this article, first we present a novel framework to deliver content in VSNs with D2D communication. In the proposed framework, moving vehicles can exchange content directly with each other according to D2D communication. All contents are managed in a content-centric mode, where moving vehicles can send their interests to obtain content with naming information, resulting in a reduction of network traffic load. Based on the D2D communication, parked vehicles around the street can form vehicular social communities with the moving vehicles passing along the road, where the storage capacity of VSNs can be increased by using the contents in parked vehicles. Then we present the detailed process of content delivery in VSNs including interest sending, content distribution, and content replacement. Finally, experiment results prove the efficiency of the proposal.

VeShare: a D2D infrastructure for real-time social-enabled vehicle networks

Vehicular social networks require real-time communication and are highly dynamic due to vehicle movement. In this article, we present a novel architecture, called VeShare, to support highly dynamic and time-sensitive social behaviors in vehicle networks. VeShare clearly separates a vehicle network into control and data planes. The control plane is managed by the cellular infrastructure. It manages the social networks over time and makes various decisions necessary for data transfer. The data plane simply forwards data, following the decision from the control plane. The clear separation of the control and data planes allows efficient social group management and data transfer. We highlight the benefits of this framework using a case study and outline a number of research challenges.

A Survey on Internet of Things for SmartVehicles

In a Smart City, all objects need to be smart hence would have embedded processors and capability to communicate with each other through wired or wireless connections .These increasingly intelligent objects would provide safe and convenient environment through growing interconnection and interoperability, which is also termed as Internet of Things (IoT), Within the objectives of IoT also lies the vehicle to smart object communications, vehicles play an important role for safe and convenient travel. The main vision of the Internet of Things (IoT) is to equip reallife physical objects with computing and communication abilities so that they can interact with each other for the social good. As one of the important members of IoT, Internet of Vehicles (IoV) has seen rapid development in communication technologies. Now, vehicles can easily exchange safety, efficiency, comfort-related information with other vehicles and infrastructures using vehicular ad hoc networks (VANETs). Where vehicles are the key social entities in the machine-to-machine vehicular social networks. The near real time applications offer safe and efficient travel of the vehicle users, and the offline data ensures smart behaviour of the vehicles and data analysis for the transport authorities. We have identified the social structures of IoV components, their relationships, and the interaction types. We have mapped VANETs components into IoT architecture reference model to offer better integration of IoV with other IoT domains. Finally, we provide the implementation details and the experimental study to demonstrate the efficiency of the proposed system as well as include different application scenarios for various user groups, practical deployment of the proposed system and using it to collect real life IoV related multi-modal sensory information in city or urban areas can be another interesting direction We envision that the IoV would be an integral part of intelligent transport systems in the future smart cities.

MixGroup: Accumulative Pseudonym Exchanging for Location Privacy Enhancement in Vehicular Social Networks

Vehicular social network (VSN) is envisioned to serve as an essential data sensing, exchanging and processing platform for the future Intelligent Transportation Systems. In this paper, we aim to address the location privacy issue in VSNs. In traditional pseudonym-based solutions, the privacy-preserving strength is mainly dependent on the number of vehicles meeting at the same occasion. We notice that an individual vehicle actually has many chances to meet several other vehicles. In most meeting occasions, there are only few vehicles appearing concurrently. Motivated by these observations, we propose a new privacy-preserving scheme, called MixGroup, which is capable of efficiently exploiting the sparse meeting opportunities for pseudonym changing. By integrating the group signature mechanism, MixGroup constructs extended pseudonym-changing regions, in which vehicles are allowed to successively exchange their pseudonyms. As a consequence, for the tracking adversary, the uncertainty of pseudonym mixture is accumulatively enlarged, and therefore location privacy preservation is considerably improved. We carry out simulations to verify the performance of MixGroup. Results indicate that MixGroup significantly outperforms the existing schemes. In addition, MixGroup is able to achieve favorable performance even in low traffic conditions.

An Architecture of Cloud-Assisted Information Dissemination in Vehicular Networks

Vehicular network technology allows vehicles to exchange real-time information between each other, which plays a vital role in the development of future intelligent transportation systems Existing research on vehicular networks assumes that each vehicle broadcasts collected information to neighboring vehicles, so that information is shared among vehicles. The fundamental problem of what information is delivered with which vehicle(s), however, has not been adequately studied. We propose an innovative cloud-assisted architecture to facilitate intelligent information dissemination among vehicles. Within the novel architecture, virtual social connections between vehicles are created and maintained on the cloud. Vehicles with similar driving histories are considered friends in a vehicular social network (VSN). The closeness of the relation between two vehicles in a VSN is then modeled by the three-valued subjective logic model. Based on the closeness between vehicles, only relevant information will be delivered to vehicles that are likely interested in it. The cloud-assisted architecture coordinates vehicular social connection construction, VSN maintenance, vehicle closeness assessment, and information dissemination.

Toward trustworthy vehicular social networks

Wireless vehicular networks offer the promise of connectivity to vehicles that could provide a myriad of safety and driving-enhancing services to drivers and passengers. With wireless technology available in each car, it is expected that huge amounts of information will be exchanged between vehicles or between vehicles and roadside infrastructure. Due to defective sensors, software viruses, or even malicious intent, legitimate vehicles might inject untrustworthy information into the network. Besides relying on the public key infrastructure, this article proposes a social network approach to study trustworthy information sharing in a vehicular network. We first cover recent research progress in measuring direct trust and modeling indirect trust in online social networks, and then discuss how to apply them to vehicular social networks despite several pressing research challenges.

S-Aframe: Agent-Based Multilayer Framework With Context-Aware Semantic Service for Vehicular Social Networks

This paper presents S-Aframe, an agent-based multilayer framework with context-aware semantic service (CSS) to support the development and deployment of context-aware applications for vehicular social networks (VSNs) formed by in-vehicle or mobile devices used by drivers, passengers, and pedestrians. The programming model of the framework incorporates features that support collaborations between mobile agents to provide communication services on behalf of owner applications, and service (or resident) agents to provide application services on mobile devices. Using this model, different self-adaptive applications and services for VSNs can be effectively developed and deployed. Built on top of the mobile devices’ operating systems, the framework architecture consists of framework service layer, software agent layer and owner application layer. Integrated with the proposed novel CSS, applications developed on the framework can autonomously and intelligently self-adapt to rapidly changing network connectivity and dynamic contexts of VSN users. A practical implementation and experimental evaluations of S-Aframe are presented to demonstrate its reliability and efficiency in terms of computation and communication performance on popular mobile devices. In addition, a VSN-based smart ride application is developed to demonstrate the functionality and practical usefulness of S-Aframe.