Application-oriented Approaches to Context-aware Mobile Crowdsensing in Vehicular Social Networks

1. MOTIVATION Mobile crowdsensing aims to provide a mechanism to involve participants from the general public to efficiently and effectively contribute and utilize context-related sensing data from their mobile devices in solving specific problems in collaborations. Also, a remarkable trend in mobile computing is the increasing use of mobile devices to access social networking services. The wide availability of sensing modules in mobile devices enables social networking services to be extended to incorporate location based services, media tag services, etc. Therefore, there is growing interest in fusing social networking services with real-world sensing, such as crowdsensing [1]. Mobile social networks (MSNs) [2] not only can provide an ideal and ubiquitous platform to enable mobile users to participate in crowdsensing, but can also help to improve the contextawareness of mobile applications and better assist users in mobile crowdsensing by analyzing and utilizing their social contexts. Vehicular social networks (VSNs) are an emerging kind of MSN for transportation applications, and a number of research works have identified that crowdsensing in VSN can be effectively used for many purposes and bring huge economic benefits, e.g., safety improvement and traffic management [3].