Abstract
Mobile crowd sensing (MCS) is a novel example of urban sensing, which uses smart phones, smart wearable devices, on-board sensors and other mobile sensor devices to collect data, and is widely used in intelligent transportation, medical care, environmental monitoring and other fields. A growing number of studies show that a good task allocation mechanism is an indispensable key factor in determining whether MCS applications can obtain good service quality. In this paper, we introduce the realistic background of MCS and combine some specific applications to exhaustively classify task allocation problems in MCS. Then, the typical algorithm for MCS task allocation is classified and illustrated. Finally, the current research challenges and future research directions are presented.
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