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Data-Oriented Mobile Crowdsensing: A Comprehensive Survey
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DOI：10.1109/COMST.2019.2910855.png)
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Mobile devices equipped with rich sensors, such as smartphones, watches, or vehicles, have been pervasively used all around the world. Their high penetration and powerful sensing ability enable them to carry out heavy sensing projects by splitting tasks into small pieces. Since ordinary participants can simply employ their mobile devices to sense and upload the required data, the mobile crowdsensing (MCS) technology is gaining great popularity. However, there are still some challenges in building a complete and sustainable MCS system. Researchers these years have proposed plenty of strategies to solve these challenges in order to improve the MCS technology. In this survey, we aim to provide a comprehensive literature review on recent advances in MCS. Oriented to the data flowing in MCS projects, we survey researches from five popular aspects in three stages: 1) incentive mechanism; 2) security protection; and 3) privacy preserving, together with resource optimization in the data collection stage; the data analysis stage; and the data application stage. To provide the convenience to interested researchers, some available testbeds, simulators, and commercial service platforms are also summarized in this survey. As the MCS technology still needs further development, we discuss some lessons learned from introduced researches as well as future research directions at last.
Keyword:
Mobile crowdsensing
incentive mechanism
privacy preserving
resource optimization
multimodal data mining
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