Crowd sensing networks play a critical role in big data generation where a large number of mobile devices collect various kinds of data with large-volume features. Although which information should be collected is essential for the success of crowd-sensing applications, few research efforts have been made so far. On the other hand, an efficient incentive mechanism is required to encourage all crowd-sensing participants, including data collectors, service providers, and service consumers, to join the networks. In this article, we propose a new incentive mechanism called QUOIN, which simultaneously ensures Quality and Usability Of INformation for crowd-sensing application requirements. We apply a Stackelberg game model to the proposed mechanism to guarantee each participant achieves a satisfactory level of profits. Performance of QUOIN is evaluated with a case study, and experimental results demonstrate that it is efficient and effective in collecting valuable information for crowd-sensing applications.

中文翻译：

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QUOIN：人群感知网络的激励机制


人群感知网络在大数据生成中发挥着至关重要的作用，其中大量移动设备收集具有大容量特征的各种数据。尽管应该收集哪些信息对于人群感知应用的成功至关重要，但迄今为止，还很少有研究工作。另一方面，需要有效的激励机制来鼓励所有众感知参与者，包括数据收集者、服务提供者和服务消费者加入网络。在本文中，我们提出了一种名为 QUOIN 的新激励机制，它同时确保信息的质量和可用性，以满足人群感知应用需求。我们将 Stackelberg 博弈模型应用于所提出的机制，以保证每个参与者都能获得满意的利润水平。通过案例研究评估了 QUOIN 的性能，实验结果表明它在为人群感知应用收集有价值的信息方面是高效且有效的。