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Staged Incentive and Punishment Mechanism for Mobile Crowd Sensing

机译:移动人群感知的分阶段激励与惩罚机制

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Having an incentive mechanism is crucial for the recruitment of mobile users to participate in a sensing task and to ensure that participants provide high-quality sensing data. In this paper, we investigate a staged incentive and punishment mechanism for mobile crowd sensing. We first divide the incentive process into two stages: the recruiting stage and the sensing stage. In the recruiting stage, we introduce the payment incentive coefficient and design a Stackelberg-based game method. The participants can be recruited via game interaction. In the sensing stage, we propose a sensing data utility algorithm in the interaction. After the sensing task, the winners can be filtered out using data utility, which is affected by time–space correlation. In particular, the participants’ reputation accumulation can be carried out based on data utility, and a punishment mechanism is presented to reduce the waste of payment costs caused by malicious participants. Finally, we conduct an extensive study of our solution based on realistic data. Extensive experiments show that compared to the existing positive auction incentive mechanism (PAIM) and reverse auction incentive mechanism (RAIM), our proposed staged incentive mechanism (SIM) can effectively extend the incentive behavior from the recruiting stage to the sensing stage. It not only achieves being a real-time incentive in both the recruiting and sensing stages but also improves the utility of sensing data.
机译:拥有激励机制对于招募移动用户参与感知任务并确保参与者提供高质量的感知数据至关重要。在本文中,我们研究了一种针对移动人群感知的分阶段的激励和惩罚机制。我们首先将激励过程分为两个阶段:征募阶段和感知阶段。在招聘阶段,我们介绍了支付激励系数并设计了基于Stackelberg的博弈方法。可以通过游戏互动来招募参与者。在感知阶段,我们提出了一种交互作用下的感知数据效用算法。完成感知任务后,可以使用数据实用程序将获胜者过滤掉,这会受到时空相关性的影响。特别是,可以基于数据效用进行参与者的信誉积累,并提出一种惩罚机制,以减少恶意参与者造成的支付成本浪费。最后,我们根据实际数据对我们的解决方案进行了广泛的研究。大量的实验表明,与现有的正向拍卖激励机制(PAIM)和反向拍卖激励机制(RAIM)相比,我们提出的分阶段激励机制(SIM)可以有效地将激励行为从招募阶段扩展到感知阶段。它不仅在招募和传感阶段都实现了实时激励,而且还提高了传感数据的实用性。

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