How effective is to look at a vehicular network under a social perception?

Vianna, Aline Carneiro; Mini, Raquel A. F.; Loureiro, Antônio A. F.

doi:10.1109/wimob.2013.6673355

Cited by 25 publications

(17 citation statements)

References 11 publications

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“…Let us assume a generic network expressed in terms of graph G (V, N ), where V and N are the sets of nodes, and edges, respectively. Based on the works in [51], [56], [57], [58], [59], and through graph theoretic and functionality models, we can distinguish the following centrality metrics: 1) Degree Centrality of a node v i.e., d (v), is the simplest centrality metric that refers to the number of direct connections the node v has to its neighbors. It can be expressed as:…”

Section: A Content Dissemination In Vsnsmentioning

confidence: 99%

“…In [58] Cunha et al present the characterization and evaluation of a realistic vehicular trace in order to study the vehicles' mobility in the context of social behaviors. Through numerical analysis, the authors identify peculiar social characteristics in vehicular networks, and how the use of these metrics can improve the network performance of communication protocols and services.…”

Section: B Social Features In Vsnsmentioning

confidence: 99%

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A Survey on Vehicular Social Networks

Vegni

Loscrì

2015

IEEE Commun. Surv. Tutorials

243

103

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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

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Section: A Content Dissemination In Vsnsmentioning

confidence: 99%

Section: B Social Features In Vsnsmentioning

confidence: 99%

A Survey on Vehicular Social Networks

Vegni

Loscrì

2015

IEEE Commun. Surv. Tutorials

243

103

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“…In our initial work [2], we showed an social analysis of a trace mobility. In this work, we had classified the metrics according to mobility features.…”

Section: Preliminary Resultsmentioning

confidence: 99%

Are vehicular networks small world?

Viana

Mini

Loureiro

2014

2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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Abstract-Daily, vehicles in transit in a city and during their trajectories encounter other vehicles. The regularity of these encounters is influenced by several elements, such as: vehicle's speed, destinations, traffic conditions, and the period of the day. It is possible to justify these elements by road conditions and the driver's behavior. People have routines and similar behaviors, which strongly impact the daily traffic evolution. An alternative to understand this evolution is to look to the vehicles' mobility under a social perspective. Thus, we present a social analysis of real and realistic traces that describe the mobility of a set of vehicles. Social metrics are computed and the obtained results are compared to random graphs. Initial results showed the presence of social characteristics in the vehicular mobility.

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“…Cunha et al [58] showed that vehicles tend to show a similar behaviour and routines in terms of mobility. The mobility of vehicles can be mapped as a social network, following the same basic laws of degree distribution and distance among nodes.…”

Section: Social Network Analysis In Siovsmentioning

confidence: 99%

Social Internet of Vehicles for Smart Cities

Μαγλαράς

Al-Bayatti

et al. 2016

JSAN

138

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Digital devices are becoming increasingly ubiquitous and interconnected. Their evolution to intelligent parts of a digital ecosystem creates novel applications with so far unresolved security issues. A particular example is a vehicle. As vehicles evolve from simple means of transportation to smart entities with new sensing and communication capabilities, they become active members of a smart city. The Internet of Vehicles (IoV) consists of vehicles that communicate with each other and with public networks through V2V (vehicle-to-vehicle), V2I (vehicle-to-infrastructure) and V2P (vehicle-to-pedestrian) interactions, which enables both the collection and the real-time sharing of critical information about the condition on the road network. The Social Internet of Things (SIoT) introduces social relationships among objects, creating a social network where the participants are not humans, but intelligent objects. In this article, we explore the concept of the Social Internet of Vehicles (SIoV), a network that enables social interactions both among vehicles and among drivers. We discuss technologies and components of the SIoV, possible applications and issues of security, privacy and trust that are likely to arise.

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How effective is to look at a vehicular network under a social perception?

Cited by 25 publications

References 11 publications

A Survey on Vehicular Social Networks

A Survey on Vehicular Social Networks

Are vehicular networks small world?

Social Internet of Vehicles for Smart Cities

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