CAREER: A New Efficient and Cooperative Large-Scale Distributed Data Sharing System

该项目研究如何使用来自社交网络的信息来创建高效和协作的大规模分布式数据共享系统。这类系统面临的两个挑战是快速且经济高效地定位数据，以及强制执行合作节点行为。基于社交网络的方法寻求将社交网络构建为数据共享系统，以利用现实世界中相互信任和共同利益的朋友属性。尽管与纯技术方法相比，这些方法可以显著降低成本和复杂性，但目前的方法只利用了非常肤浅的社会网络属性，无法支持使所有节点自由有效地共享数据的广泛目标。该项目通过更充分地利用社会网络属性，以及协调基于社会网络的方法和技术方法来解决这些缺点。研究领域包括数据搜索的基础设施、合作增强机制和数据服务器选择的算法。今天，大量的大规模分布式系统使用Internet向最终用户提供各种数据，例如软件和音频/视频内容。这些系统支持许多社会、商业和文化活动。在商业服务器上花费了数百万美元来传递这些数据。点对点技术，即用户电脑之间合作共享内容，有可能更便宜、更快地实现这一目标。然而，点对点技术的广泛应用受到一些限制。一种是节点可能行为不当，自私地接收内容但不提供回报，或者将损坏或恶意的内容分发到系统中，由毫无戒心的用户进一步传播。另一个限制是，由于节点分布广泛且缺乏中心索引，定位内容很困难。这个项目试图通过利用从社交网络获得的信息来解决这些限制。这项工作的潜在好处包括节省基础设施成本和数据分发的能源消耗。该项目还为研究生和本科生提供教育机会，并与其他教育项目合作，招收代表性不足的学生，并向K-12学生提供服务。

This project investigates how information from social networks may be used to create efficient and cooperative large-scale distributed data sharing systems. Two of the challenges facing such systems are locating data quickly and cost-efficiently, and enforcing cooperative node behaviors. Social network-based approaches seek to build social networks into data sharing systems in order to leverage the real-world friend properties of mutual trust and common interest. Although these approaches can significantly reduce cost and complexity compared to purely technical approaches, current methods only make use of a very superficial level of social network properties, and cannot support the broad goal of enabling all nodes to share data freely and efficiently. This project addresses these shortcomings through more fully leveraging social network properties, and coordinating social network-based approaches with technical approaches. Areas of investigation include infrastructures for data searching, cooperation enhancement mechanisms, and algorithms for data server selection. Today, a multitude of large-scale distributed systems use the Internet to deliver a variety of data -- such as software and audio/video content -- to end users. These systems support many social, commercial, and cultural activities. Millions of dollars are spent on commercial servers to deliver this data. Peer-to-peer technology, in which user computers cooperate to share content between themselves, has potential for doing this cheaper and faster. However, wider use of peer-to-peer technology is held back by several limitations. One is that nodes may misbehave, selfishly receiving content but not contributing in return, or distributing corrupted or malicious content into the system, to be further spread by unsuspecting users. Another limitation is that locating content is difficult, due to the wide distribution of nodes and the lack of a central index. This project seeks to address these limitations by making use of information obtained from social networks. Potential benefits of the work include savings in the costs of infrastructure and energy consumption for data distribution. The project also provides educational opportunities for graduate and undergraduate students, and collaborates with other educational programs for under-represented student recruitment, and outreach to K-12 students.