一种新的移动人群感知系统策略设计方法
A Novel Methodology for designing Policies in Mobile Crowdsensing Systems
摘要：
移动众测是一种以人为中心的感知系统，它基于用户的贡献和激励机制。在我们的工作中，我们通过博弈论方法重新思考了激励机制的设计。因此，我们引入了一个多层社会感知框架，其中人类作为社会传感器在多个社会层和各种服务上进行交互。我们已经提出了这些动态的相互作用，包括同质性的概念，我们已经建模的进化动力学的传感行为，通过定义一个数学框架的基础上，多重EGT，量化同质性，网络异质性和各种社会困境的影响。我们已经发现了导致人类合作的出现和可持续性的社会困境和网络结构的配置。此外，我们定义和评估的本地和全球纳什均衡点，包括同质性和异质性的概念。我们分析定义和测量新的统计措施的社会诚信，生活质量和用户的行为声誉分数的基础上的进化动力学。我们已经定义了决策支持系统和一个新的激励机制，通过对用户的声誉评分方面的政策，也包括用户的行为以外的质量和数量的贡献。在实验中，我们考虑了Waze数据集上的车辆交通监控应用程序，并得出了我们的方法与基线相比，奖励支出。结果表明，我们的方法，其中还包括本地（微观）的时空分布的行为，能够更好地区分用户的行为。这种多尺度的用户特征代表了一个新的研究方向，为移动人群感知系统的新政策铺平了道路。
英文摘要：
Mobile crowdsensing is a people-centric sensing system based on users' contributions and incentive mechanisms aim at stimulating them. In our work, we have rethought the design of incentive mechanisms through a game-theoretic methodology. Thus, we have introduced a multi-layer social sensing framework, where humans as social sensors interact on multiple social layers and various services. We have proposed to weigh these dynamic interactions by including the concept of homophily and we have modelled the evolutionary dynamics of sensing behaviours by defining a mathematical framework based on multiplex EGT, quantifying the impact of homophily, network heterogeneity and various social dilemmas. We have detected the configurations of social dilemmas and network structures that lead to the emergence and sustainability of human cooperation. Moreover, we have defined and evaluated local and global Nash equilibrium points by including the concepts of homophily and heterogeneity. We have analytically defined and measured novel statistical measures of social honesty, QoI and users' behavioural reputation scores based on the evolutionary dynamics. We have defined the Decision Support System and a novel incentive mechanism by operating on the policies in terms of users' reputation scores, that also incorporate users' behaviours other than quality and quantity of contributions. Experimentally, we have considered the Waze dataset on vehicular traffic monitoring application and derived the disbursement of incentives comparing our method with baselines. Results demonstrate that our methodology, which also includes the local (microscopic) spatio-temporal distribution of behaviours, is able to better discriminate users' behaviours. This multi-scale characterisation of users represents a novel research direction and paves the way for novel policies on mobile crowdsensing systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
