With the surging of smartphone sensing, wireless networking, and mobile social networking
techniques, Mobile Crowd Sensing and Computing (MCSC) has become a promising …

Sensing cost and data quality are two primary concerns in mobile crowd sensing. In this
article, we propose a new crowd sensing paradigm, sparse mobile crowd sensing, which …

Worker selection is a key issue in mobile crowd sensing (MCS). While the previous worker
selection approaches mainly focus on selecting a proper subset of workers for a single MCS …

Task allocation or participant selection is a key issue in Mobile Crowd Sensing (MCS). While
previous participant selection approaches mainly focus on selecting a proper subset of …

Mobile crowdsensing (MCS) is vulnerable to faked sensing attacks, as selfish smartphone
users sometimes provide faked sensing results to the MCS server to save their sensing costs …

Ubiquity of mobile devices with rich sensory capabilities has given rise to the mobile crowd-
sensing (MCS) concept, in which a central authority (the platform) and its participants …

Spatial crowdsourcing (SC) is an emerging paradigm of crowdsourcing, which commits
workers to move to some particular locations to perform spatio-temporal-relevant tasks (eg …

The pervasive view of the mobile crowd bridges various real-world scenes and people's
perceptions with the gathering of distributed crowdsensing photos. To elaborate informative …

Task allocation is a major challenge in Mobile Crowd Sensing (MCS). While previous task
allocation approaches follow either the opportunistic or participatory mode, this paper …

This paper has proposed an electric vehicle (EV) route selection and charging navigation
optimization model, aiming to reduce EV users' travel costs and improve the load level of the …