In this article, an online truthful mechanism is designed for mobile crowdsensing systems. Traditionally, the scenario where participants arrived at the platform in an online manner has been widely discussed in existing works. On the contrary, we focus on random task arrival case to design an online truthful mechanism by jointly considering the cost budget and the requirement of sensed data of each participant. Specifically, when the task arrives, the platform must make decisions in a sequence to select a specific number of participants to obtain a better competitive ratio (CR). To address this issue, an online strategy-proof incentive mechanism is designed to minimize the social cost of the whole system and achieve truthfulness by applying the auction framework. Moreover, in order to further improve the CR of the online algorithm, a more efficient online scheme is proposed if more information on the participants is available at the platform. Theoretical and simulation results demonstrate the effectiveness of our proposed online truthful mechanisms.

中文翻译：

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随机任务到达的群体感知在线激励机制


在本文中，为移动群智感知系统设计了一种在线真实机制。传统上，参与者以在线方式到达平台的场景在现有作品中已被广泛讨论。相反，我们专注于随机任务到达的情况，共同考虑成本预算和每个参与者感知数据的要求，设计在线真实机制。具体来说，当任务到来时，平台必须按顺序做出决策，选择特定数量的参与者，以获得更好的竞争比（CR）。为了解决这个问题，设计了一种在线策略证明激励机制，通过应用拍卖框架来最小化整个系统的社会成本并实现真实性。此外，为了进一步提高在线算法的CR，如果平台上可以获得更多关于参与者的信息，则提出更有效的在线方案。理论和模拟结果证明了我们提出的在线真实机制的有效性。