Vehicular Social Networks: A Survey
A Vehicular Social Network (VSN) is an emerging field of communication where relevant concepts are being borrowed from two different disciplines, i.e., vehicular ad-hoc networks (VANETs) and mobile social networks (MSNs). This emerging paradigm presents new research fields for content sharing, data dissemination, and delivery services. Based on social network analysis (SNA) applications and methodologies, interdependencies of network entities can be exploited in VSNs for prospective applications. VSNs involve social interactions of commuters having similar objectives, interests, or mobility patterns in the virtual community of vehicles, passengers, and drivers on the roads. In this paper, considering social networking in a vehicular environment, we investigate the prospective applications of VSNs and communication architecture. VSNs benefit from the social behaviors and mobility of nodes to develop novel recommendation systems and route planning. We present a state-of-the-art literature review on socially-aware applications of VSNs, data dissemination, and mobility modeling. Further, we give an overview of different recommendation systems and path planning protocols based on crowdsourcing and cloud-computing with future research directions.
A. Rahim et al., "Vehicular Social Networks: A Survey," Pervasive and Mobile Computing, vol. 43, pp. 96-113, Elsevier, Jan 2018.
The definitive version is available at https://doi.org/10.1016/j.pmcj.2017.12.004
Intelligent Systems Center
Keywords and Phrases
Distributed computer systems; Fiber optic sensors; Information dissemination; Motion planning; Recommender systems; Social networking (online); Transportation; Virtual reality; Communication architectures; Future research directions; Mobile social network (MSNs); Security; Selfishness; Socially aware networking; Vehicular Adhoc Networks (VANETs); Vehicular social networks; Vehicular ad hoc networks; Recommendation systems
International Standard Serial Number (ISSN)
Article - Journal
© 2018 Elsevier, All rights reserved.
01 Jan 2018