Squadron: Incentivizing Quality-Aware Mission-Driven Crowd Sensing
2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION)(2018)
摘要
Recent years have witnessed the success of mobile crowd sensing systems, which outsource sensory data collection to the public crowd equipped with various mobile devices in a wide spectrum of civilian applications. We envision that crowd sensing could as well be very useful in a whole host of mission-driven scenarios, such as peacekeeping operations, noncombatant evacuations, and humanitarian missions. However, the power of crowd sensing could not be fully unleashed in mission-driven crowd sensing (MiCS) systems, unless workers are effectively incentivized to participate. Therefore, in this paper, taking into consideration workers' diverse quality of information (QoI), we propose Squadron, a quality-aware incentive mechanism for MiCS systems. Squadron adopts the reverse auction framework. It approximately minimizes the platform's total payment for worker recruiting in a computationally efficient manner, and recruits workers who potentially could provide high quality data. Furthermore, it also satisfies the desirable properties of truthfulness and individual rationality. Through rigorous theoretical analysis, as well as extensive simulations, we validate the various aforementioned desirable properties held by Squadron.
更多查看译文
关键词
incentive mechanism, quality of information, mission-driven crowd sensing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络