DC: Small: One Thousand Points of Light: Accelerating Data-Intensive Applications By Proxy

大量的分布式数据丰富的应用程序，包括分布式数据挖掘、分布式工作流和Web 2.0 Mashup，越来越多地依赖云服务来满足其数据存储和计算需求。然而，今天，这些应用程序负责单独组合来自不同专业云服务的数据和结果，由于缺乏将应用程序连接到多个云的适当资源，这可能导致显著的性能和可靠性瓶颈，从而严重阻碍其成功部署。该项目提出了一个云代理网络，允许在战略网络位置执行优化和可靠的以数据为中心的操作。在这个模型中，代理可以承担几个以数据为中心的角色：与云服务交互，相互路由数据，缓存数据供以后使用，以及调用计算密集型数据操作符进行中间处理。拟议的解决方案将实现云服务的有效耦合，为新兴的数据密集型应用程序提供更好的端到端性能和可靠性。该项目将通过使用志愿者方法评估其优点来探索代理网络架构的潜力，重点关注四个主要研究挑战：代理性能，代理可靠性，代理信息稀疏性和代理选择。该项目的更广泛影响是放大各种科学，社会，和工程社区，以高效和可靠的方式实现数据驱动的科学探究。代理中间件将向更广泛的社区发布以实现这一目标。还提出了通过重大课程创新教育新一代学生以数据为中心的计算。

A large class of distributed data-rich applications, including distributed data mining, distributed workflows, and Web 2.0 Mashups, are increasingly relying on cloud services to meet their data storage and computing demands. However, today, these applications are responsible for combining data and results from different specialized cloud services individually, which can lead to significant performance and reliability bottlenecks, due to the lack of appropriate resources connecting the applications to multiple clouds, resulting in a significant impediment to their successful deployment. This project proposes a cloud proxy network that allows optimized and reliable data-centric operations to be performed at strategic network locations. In this model, proxies may take on several data-centric roles: interacting with cloud services, routing data to each other, caching data for later use, and invoking compute-intensive data operators for intermediate processing. The proposed solution will enable an efficient coupling of cloud services to yield improved end-to-end performance and reliability for newly emerging data-intensive applications. This project will explore the potential of the proxy network architecture by evaluating its merits using a volunteer approach, focusing on four main research challenges: Proxy Performance, Proxy Reliability, Proxy Information Sparsity, and Proxy Selection.The broader impact of this project is to amplify the effectiveness and productivity of diverse scientific, social, and engineering communities for enabling data-driven scientific inquiry in a performance-efficient and reliable manner. Proxy middleware will be released to the wider community towards this end. Educating a new generation of students in data-centric computing through major curriculum innovation is also proposed.