探讨参与式感知的可持续激励机制

Xiaoshan Sun, Jinyang Li, Wei Zheng, Hengchang Liu
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引用次数: 7

摘要

参与式传感在物联网(IoT)应用中发挥着重要作用,通过无处不在的设备的强大传感器收集大规模数据。但是,如果没有适当的激励机制对用户进行奖励,应用提供商(平台)在数据收集和上传过程中,由于成本的原因,无法保持用户的动力。此外,在数据质量重要性不同的各种应用场景中,传统的激励机制难以满足对数据质量的要求。本文从用户选择和支付分配的角度出发,提出了一种新的可持续参与式感知激励机制。它考虑了数据质量和历史参与信息,以防止用户退出。它使用户能够真实地报告成本,并方便地调整适应不同质量要求的应用。广泛的评估结果表明,我们的解决方案优于其他最先进的方法,并显著提高了系统的可持续性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a Sustainable Incentive Mechanism for Participatory Sensing
Participatory sensing plays an important role in Internet of Things (IoT) applications to collect large scale data via powerful sensors from ubiquitous devices. However, without a proper incentive mechanism to pay rewards to the users, the application provider (platform) cannot keep the motivation of users due to their costs during the data collection and uploading process. Moreover, conventional incentive mechanisms can hardly meet the requirements of data quality in various application scenarios in which the importance of data quality differs. In this paper, we present a novel incentive mechanism for sustainable participatory sensing considering the user selection and payment allocation in the long run. It takes data quality and historical participation information into account to prevent users from dropping out. It makes users report their costs truthfully and easily adjusts the adaptability to applications with different quality requirements. Extensive evaluation results demonstrate that our solution outperforms alternative state-of-the-art approaches and significantly improves system sustainability.
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