CC*IIE Integration: Dynamically Optimizing Research Data Workflow with a Software Defined Science Network

校园科研网络的智能管理已成为许多机构面临的一个重大挑战，因为他们的网络规模和复杂性迅速增长，以满足校园科学家进行研究，与同行合作，并履行其科学教育的使命的需求。传统的、静态的网络管理方法已不再适用，因为它们常常导致效率低、可用性差和不可预测的网络应用性能。该项目的目标是设计和部署一种新型的智能网络网络基础设施，大大扩展科学家快速有效地移动计算和数据密集型科学工作流程所需的大量数据的能力。为了确保广泛的影响，该项目特别关注天文学、气候学和基因组学等不同领域的一系列科学驱动因素。该项目通过利用和验证先前的几项网络研究和开发工作来实现其目标。其中包括Maple，一种在耶鲁开发的新型软件定义网络（SDN）编程框架，以及在耶鲁开创的应用层流量优化（ALTO）协议和框架，现在被互联网工程任务组纳入互联网的拟议标准。Maple简化了端到端、复杂、动态构建的网络服务的网络编程，而ALTO使网络应用程序能够根据网络状态进行动态调整，以提供网络效率和应用程序服务质量。此外，该项目建立在耶鲁大学和NSF之前对高速物理网络网络基础设施、广泛采用的InCommon认证框架和IPv6技术的投资基础上。

Intelligent management of campus research networks has become a major challenge for many institutions, as their networks grow rapidly in size and complexity in order to meet the demands of on-campus scientists who are conducting research, collaborating with peers, and fulfilling their mission of scientific education. Traditional, static network management approaches are no longer adequate, since they often result in low efficiency, poor usability, and unpredictable network application performance. The goal of this project is to design and deploy a novel intelligent network cyberinfrastructure that greatly expands the ability of scientists to rapidly and efficiently move the large quantities of data required for computation- and data-intensive scientific workflows. To ensure a broad impact, the project includes specific focus on a range of science drivers in diverse fields such as astronomy, climatology, and genomics. The project achieves its goal by leveraging and validating several prior networking research and development efforts. These include Maple, a novel Software Defined Networking (SDN) programming framework developed at Yale, and an Application Layer Traffic Optimization (ALTO) protocol and framework pioneered at Yale and now incorporated in a proposed standard for the Internet by the Internet Engineering Task Force. Maple simplifies network programming for end-to-end, complex, dynamically constructed network services, while ALTO enables network applications to adapt dynamically, according to network states, to deliver network efficiency and application quality of service. In addition, the project builds on prior Yale and NSF investments in high-speed physical network cyberinfrastructure, the widely-adopted InCommon authentication framework, and IPv6 technology.