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: 0915928
• 负责人: Gustavo de Veciana
• 金额: $ 15万
• 依托单位: University of Texas at Austin
• 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=0915928&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-网络：小：协作研究：支持非结构化的点对点社交网络09/01/09-08/31/12G。 De Veciana，PI，U.T。 Austin和G. kesidis，Pi，Penn Stateaward摘要：点对点系统在流量量以及作为构建新应用程序和网络服务的架构方面持续增长？显着的好处在于它们的分布式设计，从而带来更高的可靠性和灵活性。但是，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时，隐私是一个关键问题。通过利用同行？通过基于基本信誉系统的转诊机制的信任关系，正在设计提供新的隐私标准的应用程序。基于对等交易的结果，以分布式和可扩展方式动态适应的对等系统正在建模和分析。重点是非结构化的网络，可以学会在这些网络中同行会员之间的相关性，以提高声誉偏见的随机步行和有限范围洪水的搜索性能。正在设计内容共享应用程序，以利用此框架来激励合作行为，同时启用协作过滤和内容推动。预期的结果包括开发分析和测试新的框架，以保护隐私范围，以搜索大型，非结构化的，非结构化的，在线，在线，对等网络。将设计互补的激励机制，从而改善文件共享和促进诚实推荐。结果将通过经过同行评审的场地以及行业的关注，而在网络上提供数据和仿真工具时进行分散。努力的影响将在于有助于提高隐私和在大型在线点对点系统中进行更诚实和高效的合作的新方法，以及用于内容共享以及社交网络设置的广泛集合。