Abstract
Mobile crowd sensing (MCS) is a computing paradigm that recruits citizens to collect and contribute sensing data from surroundings using their smart device. The incentive mechanisms and task allocation methods are critical parts that affect whether the MSC campaigns could continue gaining sensing data. In this paper, we survey the literature over the period of 2018–2020 from the state-of-the-art of incentive mechanism and task allocation method design in MCS.
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