Cyber-physical social system (CPSS) has emerged as a new paradigm to help social users share and exchange data by the close association with the cyberspace and physical world. To further improve the performance of CPSS, the incentive computing scheme to provide efficient crowd sourcing in the CPPS becomes a challenge. Therefore, in this paper we propose a novel incentive scheme for CPSS based on the reputation of social users. First, we present a framework to provide crowd sourcing service in CPSS by dividing social users into three types, which are malicious users, speculative users and honest users, respectively. Second, based on the reputation of social users, an incentive scheme is proposed to encourage users to contribute sourcing data. Next, an auction game model is developed to help CPSS select the optimal social user to obtain the needed data. Finally, simulation results show that the proposal can obtain a lower cost and higher data accuracy than other conventional methods.

中文翻译：

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基于用户行为的网络物理社交系统激励方案

网络物理社会系统（CPSS）作为一种新的范式出现，通过与网络空间和物理世界的密切联系，帮助社会用户共享和交换数据。为了进一步提高 CPSS 的性能，在 CPPS 中提供高效众包的激励计算方案成为一个挑战。因此，在本文中，我们提出了一种基于社会用户声誉的新型 CPSS 激励方案。首先，我们通过将社交用户分为恶意用户、投机用户和诚实用户三类，提出了一个在 CPSS 中提供众包服务的框架。其次，基于社会用户的声誉，提出激励方案，鼓励用户贡献源数据。下一个，开发了拍卖博弈模型来帮助 CPSS 选择最佳社交用户以获得所需的数据。最后，仿真结果表明，与其他传统方法相比，该建议可以获得更低的成本和更高的数据精度。