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Fig. 1 Overview of the mobile crowdsensing system.
A typical mobile crowdsensing system is shown in Fig. 1.
In this paper, we study a critical problem of payoff maximization in mobile crowdsensing system with incentive mechanism.
Reddy et al. [90] highlighted these three factors as the key performance metrics of any mobile crowdsensing system.
Hence, there is need for a deeper investigation into the implications of allowing both monetary and non-monetary incentive mechanisms to co-exist and be used concurrently to reward participants in the same mobile crowdsensing system.
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In this paper we identify basic design issues of Mobile Crowdsensing Systems and investigate some characteristic challenges.
This is crucial because failing to offer incentives that are worth performing the sensing tasks can lead to poor adoption of mobile crowdsensing systems [1].
Furthermore, privacy of mobile crowdsensing systems is still in its infancy and requirements may vary slightly depending on the area of application [24].
Data collection (including request collection from the data requesters and data collection from the data providers) is an essential block to build mobile crowdsensing systems [6, 7].
GroupMe, proposed in [124] is a giant stride in this direction to help facilitate the discovery of groups within mobile crowdsensing systems.
Service incentive is a non-monetary reward system wherein participants in mobile crowdsensing systems are asked to contribute sensed data in return for service usage [1].
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