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

0915928-网络：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，U.T.Austin和G.Kesidis，Pi，Penn State奖摘要：对等系统在通信量方面持续增长，并成为构建新应用程序和网络服务的首选架构？显著的好处在于它们的分布式设计带来了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，并通常在网络上进行更多的业务，隐私是一个关键问题。通过基于基本声誉系统的推荐机制，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，以分布式和可扩展的方式动态适应的对等系统正在被建模和分析。重点放在非结构化网络上，在这些网络中，可以学习感兴趣社区之间的对等成员相关性，以改善基于声誉的随机行走和有限范围洪泛的搜索性能。正在设计的内容共享应用程序利用该框架来激励合作行为，同时支持协作过滤和内容推送。预期的结果包括开发分析和测试用于大规模、非结构化、在线、对等网络的隐私保护搜索的新框架。将制定补充激励机制，以改善文件共享和促进诚实转介。结果将通过同行审查的场所传播，并在可能的情况下，通过业界关注的问题，同时在网络上提供数据和模拟工具。努力的影响将在于提供新的方法来改善隐私，并促进大规模在线对等系统、内容共享以及更广泛的社交网络应用程序中更诚实和更有效的合作。

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.