移动社交网络的机会信息共享机制研究

The past years witness the rapid development of mobile communication technology and social network applications. On one hand, mobile devices such as smartphones and tablets are quickly becoming the prominent platforms for user communication and information services. On the other hand, the prevailing social network applications such as Facebook, Twitter, Renren and Sina Weibo have become the most important source of social media. Information sharing is a basic function of social network applications. This project studies the key techniques and mechanisms of using opportunistic communication for information sharing among mobile devices. Opportunistic communication is independent of infrastructure and it exploits ad hoc communication and mobility of users to achieve non-realtime data dissemination, which encounters the problems of the scarcity of network and the unpredictable of communication opportunities. We incorporate user social properties to optimize information sharing in mobile social networks. First, based on social network analysis, we construct a three dimensional model to describe mobile users from the perspectives of friendship, mobility patterns and information access interests. Then we study the key optimization techniques of information sharing, including the community-based cooperative data caching strategies and mobility-assisted opportunistic data forwarding strategies. Finally, we combine the above schemes to form a comprehensive cooperative information sharing system for mobile social networks and evaluate its performance using smartphones.

近年来，移动通信技术和社交网络应用迅速发展。一方面，移动通信设备如智能手机和平板电脑等日渐普及，成为人们通信交流和访问信息服务的主要平台。另一方面，社交网络如脸书，推特，人人网，新浪微博等迅速兴起，成为人们获取社会新闻的重要来源。信息共享是社交网络的基本功能，本项目研究移动设备通过机会通信来实现信息共享的关键技术和机理。机会通信不依赖于基础设施，通过点到点通信和节点的移动性来实现非实时信息传输，其难点在于网络的稀疏性和通信机会的不可预测性。本项目结合社交网络用户的社会特征优化社交网络的机会信息共享。首先，基于社交网络分析，从好友关系，运动模式和信息访问兴趣三个方面，建立用户的三维信息模型。其次，基于三维信息模型，研究优化信息共享的关键技术，包括基于社群的协同数据缓存技术和基于运动模式的机会转发技术。最后，综合各方面优化结果，形成高效的移动社交网络信息共享体系并在智能手机上进行性能评估。

本项目研究移动设备通过机会通信来实现信息共享的关键技术和机理。主要研究内容和成果包括以下方面。首先，面向移动社交网络，提出了网络结构分析、影响力分析和社群检测等技术，并从好友关系，运动模式和信息访问兴趣三个方面，建立用户的三维信息模型。其次，研究了移动社交网络中基于社群的协同数据缓存和机会传输优化关键技术。再次，提出了基于移动模式和社交属性的机会数据转发和信息共享策略。最后，综合各方面优化结果，形成高效的移动社交网络信息共享体系并在智能手机上进行性能评估。. 以本项目工作为基础，课题组成员在包括《IEEE Transactions on Parallel and Distributed Systems》，《IEEE Communications Magazine》，《IEEE/ACM Transactions on Networking》， INFOCOM 2015，PERCOM 2016，SECON 2016等国际期刊和国际会议录用和发表论文 23篇，其中 SCI 检索论文10篇，CCF-A类论文5篇，CCF-B类论文7篇。提交国家专利申请 3项。发表英文专著2章节。

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