移动社交中感知数据收集的机会路由与交互式内容移交

项目名称： 移动社交中感知数据收集的机会路由与交互式内容移交

项目编号： No.61332005

项目类型： 重点项目

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： 马华东

作者单位： 北京邮电大学

项目金额： 320万元

中文摘要： 移动社交网络就是利用携带移动感知设备的参与用户之间的相互协作，以无线多跳的通讯方式形成的一种群体感知系统，完成大规模的、复杂的群智感知任务。本项目根据移动社交网络用户参与广泛性、数据感知连续性、网络状态弱连接性、感知数据的丰富性等特点，重点研究移动社交网络机会路由算法、交互式内容移交方法、用户激励机制等，解决感知数据的时效转发、富内容的选择移交以及用户参与的个性化激励等关键科学问题，以移动社交网络为载体研究群智感知与群智计算的理论与方法，取得一批高水平的学术成果，丰富物联网的理论体系。利用本项目对移动社交网络中感知数据收集的机会路由与交互式内容移交的理论成果为基础，形成一系列关键技术和创新的自主知识产权，在城市管理突发事件应急处理等方面开展应用验证，推动物联网更深入和广泛的应用，有力支撑物联网发展的国家战略。

中文关键词： 移动社交网络;机会路由;内容移交;群智计算;

英文摘要： Mobile social network is a kind of crowd sensing systems, which utilizes the collaboration among users with mobile devices to execute the large-scale and complicated sensing tasks by multi-hop wireless communication. Considering several important characteristics of mobile social networks, such as pervasive user participations, continuous data sensing, weak interconnectivity of network, and richness of sensory data, we mainly study opportunistic routing, interactive content delivery and user incentive mechanism in mobile social network to solve several key scientific problems including efficient forwarding of sensory data, selective transferring of rich contents, individualized incentive mechanism for user participation, etc.. We investigate the theories and methods of crowd sensing and crowd computing based on mobile social networks, and aim to obtain the novel research results to enrich the theoretical architecture of IoT. Based on the theoretical achievements such as opportunistic data collection and interactive content delivery in the mobile social networks, we will further achieve a series of key technologies and independent intellectual properties, and develop the typical application, like emergency response and treatment in urban management, to verify these theoretical results. This project will promote more general applications of IoT, and will strongly support the national strategy of IoT development.

英文关键词： Mobile Social Network;Opportunistic Routing ;Content Delivery ;Crowd Computing