CAREER: Socially-Aware Distributed Systems

最近，集体智慧被用来创造以前无法实现的新的合作形式。这种社会涌现的智能出现在信息的协作管理和索引，撰写百科全书文章，参与博客，标记或评论照片或视频中。这种社会涌现的运动也暴露了前所未有的社会信息量。特别地，两类互联网应用揭示了大量的社会信息：流行的在线社交网络（例如，Facebook或LinkedIn）;以及广泛采用的协作工具（例如，CiteULike或Delicious），通过标签、注释和文本组织提供丰富的信息结构。该项目研究了在社区支持的对等分布式基础设施的设计中包括社会知识的潜力。它将设计、原型化和评估一个面向社区的点对点基础设施，该基础设施将利用社会知识提供数据和计算管理等服务，同时保护被视为上下文完整性的社会数据隐私。基于以下假设，在服务设计中使用社会知识可能会提高性能：社会激励减少流失;社会推断的信任减少安全漏洞并扩大可用资源集;共享兴趣改善数据放置决策或数据和计算的协同定位。这将创造新的应用程序和基础设施类别的潜力。该项目开发了创新的教学策略，促进非计算机专业的学生在他们的职业生活中使用计算工具。这将通过本科入门课程的多学科合作教学，以及计算机科学和社会科学独立研究生课程的协调教学来完成。

Collective intelligence has been harnessed recently to create new collaborative forms that were not previously achievable. This socially-emergent intelligence appears in collaborative management and indexing of information, authoring encyclopedia articles, participating in blogs, tagging or commenting photographs or videos. This socially-emergent movement also exposes an unprecedented amount of social information. Particularly, two classes of Internet applications reveal voluminous social information: popular online social networks (e.g., Facebook or LinkedIn); and the widely-adopted collaborative tools (e.g., CiteULike or Delicious) that provide rich information fabric through tags, annotations, and text organization.This project investigates the potential of including social knowledge in the design of community-enabled peer-to-peer distributed infrastructures. It will design, prototype, and evaluate a community-oriented peer-to-peer infrastructure that exploits social knowledge for services such as data and computing management, while protecting social data privacy seen as contextual integrity. Using social knowledge in the design of services will likely improve performance, based on the assumptions that social incentives reduce churn; socially-inferred trust reduce security breaches and expand the set of available resources; and shared interest improves data placement decisions or co-location of data and computations. This will create the potential to enable new classes of applications and infrastructures. This project develops innovative teaching strategies that facilitate non CS-major students use of computational tools in their professional lives. This will be done through multidisciplinary co-teaching of an undergraduate introductory course, and coordinated teaching of independent graduate courses in computer science and social sciences.