Vehicular Social Networks: Enabling Smart Mobility
TL;DR: An application scenario on trajectory data-analysis-based traffic anomaly detection for VSNs and several research challenges and open issues are highlighted and discussed.
Abstract: 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.
Citations
More filters
TL;DR: A conceptual, generic, and expandable framework for classifying the existing PLS techniques against wireless passive eavesdropping is proposed, and the security techniques that are reviewed are divided into two primary approaches: signal-to-interference-plus-noise ratio- based approach and complexity-based approach.
Abstract: Physical layer security (PLS) has emerged as a new concept and powerful alternative that can complement and may even replace encryption-based approaches, which entail many hurdles and practical problems for future wireless systems. The basic idea of PLS is to exploit the characteristics of the wireless channel and its impairments including noise, fading, interference, dispersion, diversity, etc. in order to ensure the ability of the intended user to successfully perform data decoding while preventing eavesdroppers from doing so. Thus, the main design goal of PLS is to increase the performance difference between the link of the legitimate receiver and that of the eavesdropper by using well-designed transmission schemes. In this survey, we propose a conceptual, generic, and expandable framework for classifying the existing PLS techniques against wireless passive eavesdropping. In this flexible framework, the security techniques that we comprehensively review in this treatise are divided into two primary approaches: signal-to-interference-plus-noise ratio-based approach and complexity-based approach. The first approach is classified into three major categories: first, secrecy channel codes-based schemes; second, security techniques based on channel adaptation; third, schemes based on injecting interfering artificial (noise/jamming) signals along with the transmitted information signals. The second approach (complexity-based), which is associated with the mechanisms of extracting secret sequences from the shared channel, is classified into two main categories based on which layer the secret sequence obtained by channel quantization is applied on. The techniques belonging to each one of these categories are divided and classified into three main signal domains: time, frequency and space. For each one of these domains, several examples are given and illustrated along with the review of the state-of-the-art security advances in each domain. Moreover, the advantages and disadvantages of each approach alongside the lessons learned from existing research works are stated and discussed. The recent applications of PLS techniques to different emerging communication systems such as visible light communication, body area network, power line communication, Internet of Things, smart grid, mm-Wave, cognitive radio, vehicular ad-hoc network, unmanned aerial vehicle, ultra-wideband, device-to-device, radio-frequency identification, index modulation, and 5G non-orthogonal multiple access based-systems, are also reviewed and discussed. The paper is concluded with recommendations and future research directions for designing robust, efficient and strong security methods for current and future wireless systems.
457 citations
TL;DR: An iterative heuristic MEC resource allocation algorithm to make the offloading decision dynamically and results demonstrate that the algorithm outperforms the existing schemes in terms of execution latency and offloading efficiency.
Abstract: With the evolutionary development of latency sensitive applications, delay restriction is becoming an obstacle to run sophisticated applications on mobile devices. Partial computation offloading is promising to enable these applications to execute on mobile user equipments with low latency. However, most of the existing researches focus on either cloud computing or mobile edge computing (MEC) to offload tasks. In this paper, we comprehensively consider both of them and it is an early effort to study the cooperation of cloud computing and MEC in Internet of Things. We start from the single user computation offloading problem, where the MEC resources are not constrained. It can be solved by the branch and bound algorithm. Later on, the multiuser computation offloading problem is formulated as a mixed integer linear programming problem by considering resource competition among mobile users, which is NP-hard. Due to the computation complexity of the formulated problem, we design an iterative heuristic MEC resource allocation algorithm to make the offloading decision dynamically. Simulation results demonstrate that our algorithm outperforms the existing schemes in terms of execution latency and offloading efficiency.
383 citations
Cites background from "Vehicular Social Networks: Enabling..."
...Strict delay restrictions have become an obstacle to run sophisticated applications on mobile devices [4], with the result that UEs cannot handle large amounts of computing tasks in a short period of time....
[...]
TL;DR: A feasible solution that enables offloading for real-time traffic management in fog-based IoV systems, aiming to minimize the average response time for events reported by vehicles is put forward.
Abstract: Fog computing has been merged with Internet of Vehicle (IoV) systems to provide computational resources for end users, by which low latency can be guaranteed. In this paper, we put forward a feasible solution that enables offloading for real-time traffic management in fog-based IoV systems, aiming to minimize the average response time for events reported by vehicles. First, we construct a distributed city-wide traffic management system, in which vehicles close to road side units can be utilized as fog nodes. Then, we model parked and moving vehicle-based fog nodes according to a queueing theory, and draw the conclusion that moving vehicle-based fog nodes can be modeled as an $M/M/1$ queue. An approximate approach is developed to solve the offloading optimization problem by decomposing it into two subproblems and scheduling traffic flows among different fog nodes. Performance analyses based on a real-world taxi-trajectory datasets are conducted to illustrate the superiority of our method.
320 citations
Cites background from "Vehicular Social Networks: Enabling..."
...Real-time resource management is important in fog-based vehicular networks, because the transmission delay is the main challenge for the deployment of large-scale traffic management systems [20]....
[...]
TL;DR: In this paper, a special issue on "Understanding Smart Cities: Innovation Ecosystems, Technological Advancements, and Societal Challenges" is presented, where the authors take stock of past work and provide new insights through the lenses of a hybrid framework.
294 citations
TL;DR: This work studies a trajectory-based interaction time prediction algorithm to cope with an unstable network topology and high rate of disconnection in SIoVs and proposes a cooperative quality-aware system model, which focuses on a reliability assurance strategy and quality optimization method.
Abstract: Because of the enormous potential to guarantee road safety and improve driving experience, social Internet of Vehicle (SIoV) is becoming a hot research topic in both academic and industrial circles. As the ever-increasing variety, quantity, and intelligence of on-board equipment, along with the ever-growing demand for service quality of automobiles, the way to provide users with a range of security-related and user-oriented vehicular applications has become significant. This paper concentrates on the design of a service access system in SIoVs, which focuses on a reliability assurance strategy and quality optimization method. First, in lieu of the instability of vehicular devices, a dynamic access service evaluation scheme is investigated, which explores the potential relevance of vehicles by constructing their social relationships. Next, this work studies a trajectory-based interaction time prediction algorithm to cope with an unstable network topology and high rate of disconnection in SIoVs. At last, a cooperative quality-aware system model is proposed for service access in SIoVs. Simulation results demonstrate the effectiveness of the proposed scheme.
254 citations
Cites background from "Vehicular Social Networks: Enabling..."
...[13] attempt to reveal the mobility patterns and...
[...]
References
More filters
TL;DR: A systematic survey on the major research into trajectory data mining, providing a panorama of the field as well as the scope of its research topics, and introduces the methods that transform trajectories into other data formats, such as graphs, matrices, and tensors.
Abstract: The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Many techniques have been proposed for processing, managing, and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into trajectory data mining, providing a panorama of the field as well as the scope of its research topics. Following a road map from the derivation of trajectory data, to trajectory data preprocessing, to trajectory data management, and to a variety of mining tasks (such as trajectory pattern mining, outlier detection, and trajectory classification), the survey explores the connections, correlations, and differences among these existing techniques. This survey also introduces the methods that transform trajectories into other data formats, such as graphs, matrices, and tensors, to which more data mining and machine learning techniques can be applied. Finally, some public trajectory datasets are presented. This survey can help shape the field of trajectory data mining, providing a quick understanding of this field to the community.
1,289 citations
"Vehicular Social Networks: Enabling..." refers background in this paper
...Table 2 demonstrates the taxonomy of VSN applications, which can be further divided into social-data-driven vehicular networks, social vehicular ad hoc networks (VANETs), and data-driven social networks [4]....
[...]
...However, trajectories of vehicles are not perfectly accurate due to sensor noise and other reasons, for example, false positioning signals received in some urban areas [4]....
[...]
TL;DR: The unique features and novel application areas of MCSC are characterized and a reference framework for building human-in-the-loop MCSC systems is proposed, which clarifies the complementary nature of human and machine intelligence and envision the potential of deep-fused human--machine systems.
Abstract: With the surging of smartphone sensing, wireless networking, and mobile social networking techniques, Mobile Crowd Sensing and Computing (MCSC) has become a promising paradigm for cross-space and large-scale sensing. MCSC extends the vision of participatory sensing by leveraging both participatory sensory data from mobile devices (offline) and user-contributed data from mobile social networking services (online). Further, it explores the complementary roles and presents the fusion/collaboration of machine and human intelligence in the crowd sensing and computing processes. This article characterizes the unique features and novel application areas of MCSC and proposes a reference framework for building human-in-the-loop MCSC systems. We further clarify the complementary nature of human and machine intelligence and envision the potential of deep-fused human--machine systems. We conclude by discussing the limitations, open issues, and research opportunities of MCSC.
650 citations
TL;DR: This article proposes a multi-layered context-aware architecture and introduces two crucial service components, vehicular social networks and context- aware vehicular security, and proposes an application scenario regarding the context- Aware dynamic parking services by illuminating the cloud-assisted architecture and logic flow.
Abstract: The advances in wireless communication techniques, mobile cloud computing, and context- aware technologies boost a growing interest in the design, development, and deployment of vehicular networks for emerging applications. This leads to an increasing evolutionary tendency to change from vehicular networks toward cloud-assisted context-aware vehicular cyberphysical systems. In this article, we first propose a multi-layered context-aware architecture and introduce two crucial service components, vehicular social networks and context-aware vehicular security. Then we propose an application scenario regarding the context-aware dynamic parking services by illuminating the cloud-assisted architecture and logic flow. Finally, we investigate the challenges and possible solutions, including context-aware safety hazard prediction, context-aware dynamic vehicle routing, and context-aware vehicular clouds.
340 citations
"Vehicular Social Networks: Enabling..." refers background in this paper
...[6] investigated an architecture supported by mobile cloud for the vehicular cyber-physical system, and designed a context-aware dynamic parking service for smart cities as a case....
[...]
TL;DR: A survey on main features of vehicular social networks, from novel emerging technologies to social aspects used for mobile applications, as well as main issues and challenges is provided.
Abstract: This paper surveys recent literature on vehicular social networks that are a particular class of vehicular ad hoc networks, characterized by social aspects and features. Starting from this pillar, we investigate perspectives on next-generation vehicles under the assumption of social networking for vehicular applications (i.e., safety and entertainment applications). This paper plays a role as a starting point about socially inspired vehicles and mainly related applications, as well as communication techniques. Vehicular communications can be considered the “first social network for automobiles” since each driver can share data with other neighbors. For instance, heavy traffic is a common occurrence in some areas on the roads (e.g., at intersections, taxi loading/unloading areas, and so on); as a consequence, roads become a popular social place for vehicles to connect to each other. Human factors are then involved in vehicular ad hoc networks, not only due to the safety-related applications but also for entertainment purposes. Social characteristics and human behavior largely impact on vehicular ad hoc networks, and this arises to the vehicular social networks, which are formed when vehicles (individuals) “socialize” and share common interests. In this paper, we provide a survey on main features of vehicular social networks, from novel emerging technologies to social aspects used for mobile applications, as well as main issues and challenges. Vehicular social networks are described as decentralized opportunistic communication networks formed among vehicles. They exploit mobility aspects, and basics of traditional social networks , in order to create novel approaches of message exchange through the detection of dynamic social structures. An overview of the main state-of-the-art on safety and entertainment applications relying on social networking solutions is also provided.
236 citations
"Vehicular Social Networks: Enabling..." refers background in this paper
...Although VSN is a brand-new communication paradigm with interest from both academia and industry, the convergence of social networks with IoVs is still in its infancy....
[...]
...The architecture of VSNs is flexible, including: centralized architecture, where a centralized server manages the system enabling V2I communication; decentralized architecture, where V2V communication is carried out opportunistically via DSRC or WAVE; and hybrid architecture, where users can be connected to the Internet via cellular networks like third/fourth generation (3G/4G) through RSUs. chArActerIstIcs oF Vsns VSNs could be broadly leveraged in smart cities since they can obtain individuals’ social relationships through network analysis, and extend users’ social activities in IoVs by providing data services....
[...]
...The integration of intelligent sensors and communication technologies opens up an entirely new frontier for IoVs in smart cities since vehicles have changed dramatically....
[...]
...From IoVs to Vsns For the sake of information dissemination and connectivity improvement, opportunistic routing has been extended into IoVs, whose applications have natural contact with social networks....
[...]
...Although VSNs can be regarded as the integration of social networks and IoVs to improve the quality of life for citizens, the avenues of VSN studies are not flat, and many open issues are still ahead....
[...]
TL;DR: This paper proposes a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion and addresses the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV.
Abstract: The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.
206 citations
"Vehicular Social Networks: Enabling..." refers background in this paper
...Since traffic prediction and congestion alleviation are important for smart cities, a mobile crowdsensing-based scheme was presented for dynamic route selection [14]....
[...]