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Mobile crowdsensing enables individuals to collect data from social events and phenomena for performing tasks released by customers using their mobile devices. It removes the necessity of sensors deployment and hence supports large-scale sensing applications efficiently. Nevertheless, incentive and privacy remain as the major obstacles that need additional attention. If privacy is not presered or...
Mobile crowdsensing is a new paradigm which explores the mobility and intelligence of mobile users to collect high-quality data from social events and phenomena for conducting complex sensing tasks. Nevertheless, privacy preservation and task allocation become main obstacles that need additional attention. To achieve accurate task allocation, it is inevitable to share some sensitive information of...
It is challenging to improve the performance of WBANs in a mobile social environment due to mobility, privacy concerns, and dynamic social interactions. Mobile social networks are capable of providing an opportunity to address the challenge for rapidly increasing m-Health applications. In this article we propose to construct new algorithms and theoretical models to build s-WBANs that can bridge the...
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