NeTS: Small: Collaborative Research: Supporting unstructured peer-to-peer social networking

NetS：小型：协作研究：支持非结构化点对点社交网络

• 批准号: 0916179
• 负责人: George Kesidis
• 金额: $ 15万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916179&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Supporting

0915928 - NeTS: Small: Collaborative Research: Supporting unstructured peer-to-peer social networking09/01/09-08/31/12G. de Veciana, PI, U.T. Austin, and G. Kesidis, PI, Penn StateAward Abstract:Peer-to-peer systems have seen continued growth, in terms of traffic volume, and as the architecture of choice to build new applications and network services ? notable benefits lie in their distributed design leading to higher reliability and flexibility. However as users/peers increasingly become content providers, and generally conduct more of their business on the network, privacy is a critical concern.By leveraging peers? trust relationships through referral mechanisms based on underlying reputation systems, applications that deliver a new standard of privacy are being devised. Peer-to-peer systems that dynamically adapt, in a distributed and scalable manner, based on the outcomes of peer transactions, are being modeled and analyzed. The focus is on unstructured networks where peer-membership correlations among communities of interest can be learned to improve the search performance of reputation-biased random walks and limited-scope flooding. Content-sharing applications are being designed based that leverage this framework to incentivize cooperative behavior while enabling collaborative filtering and content pushing.Expected results include the development analysis and testing of a new framework for privacy-preserving search for large-scale, unstructured, on-line, peer-to-peer networks. Complementary incentive mechanisms resulting in improve file sharing and promoting honest referrals will be devised. The results will be disseminated through peer-reviewed venues and, where possible, industry concerns, while data and simulation tools are made available on the web.The efforts impact will lie in contributing new ways to improve privacy and promote more honest and efficient cooperation in large-scale on-line peer-to-peer systems, for content sharing, as well as a broader set of social networking applications.

0915928 - NetS：小型：协作研究：支持非结构化点对点社交网络09/01/09-08/31/12G。 de Veciana，PI，UT Austin 和 G. Kesidis，PI，宾夕法尼亚州立大学奖 摘要：点对点系统在流量方面持续增长，并且作为构建新应用程序和网络服务的首选架构？显着的优点在于其分布式设计带来更高的可靠性和灵活性。然而，随着用户/同行越来越多地成为内容提供商，并且通常在网络上开展更多业务，隐私成为一个关键问题。通过利用同行？通过基于底层信誉系统的推荐机制建立信任关系，正在设计提供新隐私标准的应用程序。正在对基于对等交易结果以分布式和可扩展方式动态适应的对等系统进行建模和分析。重点是非结构化网络，在该网络中，可以学习感兴趣社区之间的同伴成员关系，以提高声誉偏向随机游走和有限范围洪泛的搜索性能。 正在设计内容共享应用程序，利用该框架来激励合作行为，同时实现协作过滤和内容推送。预期结果包括对用于大规模、非结构化、在线隐私保护搜索的新框架进行开发分析和测试。线路、点对点网络。将设计补充激励机制，以改善文件共享并促进诚实推荐。结果将通过同行评审的场所进行传播，并在可能的情况下通过行业关注进行传播，同时在网络上提供数据和模拟工具。这些努力的影响将在于提供新的方法来改善隐私并促进更诚实和有效的合作用于内容共享的大型在线点对点系统以及更广泛的社交网络应用程序。