位置相关众感任务的群组构建方法研究

项目名称： 位置相关众感任务的群组构建方法研究

项目编号： No.61300103

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 於志勇

作者单位： 福州大学

项目金额： 27万元

中文摘要： 随着Web 2.0、智能手机、全球定位系统、可定制地图等技术的日趋成熟和流行，一种基于大众的感知系统蔚然兴起，被称为大众感知（众感)系统。众感系统的主要目的在于，利用大量而广泛的用户及其便携设备的移动、计算、通信和感知能力，实时实地监测社会或环境中具有重要意义的事件与状态。在众感系统中，只有满足特定约束的群组，才能高质量低代价地完成众感任务。本项目旨在研究位置约束下的群组构建方法，使得用户与任务合理匹配，从而高效完成位置相关众感任务。具体研究内容包括：（1）群组位置约束模型；（2）用户位置预测算法；（3）最优群组搜索策略。本研究意义在于通过群组位置约束模型和用户位置预测算法，找出可执行众感任务的理想群组，从而避免用户选择困扰，预知并控制任务质量，并减少资源浪费，为环境监测、灾难管理、智能交通、公共安全、健康卫生等国家重大战略需求的应用领域提供理论和技术支持。

中文关键词： 群组构建；众感；位置相关；基于位置的社交网络；

英文摘要： With gradually maturing and prevalence of technologies such as Web 2.0, smartphones, Global Position System, and customized maps, a type of sensing system based on crowds of people becomes common practice, which is called Crowdsensing. The aim of crowdsensing is to monitor the significant events and states of the society or environment on the spot, by utilizing the users' and their portable devices' ability of moving, computing, communicating and sensing. Only the team that satisfies particular constraints can complete a crowdsensing task with high quality and low cost. This project will research the method of team formation under location constraints, in order to match users with tasks suitably, thus can achieve location-aware crowdsensing tasks efficiently. In detail, we will study: (1) team location constraint model, (2) user location prediction algorithm, and (3) optimum team searching strategy. The significance of this research is that with team location constraint model and user location prediction algorithm, the ideal team to perform a crowdsensing task can be found, therefore able to avoid users' choice anxiety, foresee and control the task quality, and reduce the wasting of resources. The results would provide theory and technology support for applications with national critical demands such as environm

英文关键词： Team Formation；Crowdsensing；Location-Aware；Location-Based Social Networks；