CC* Integration-Large: An Extensible Internet for Science Applications and Beyond

CC* Integration-Large：用于科学应用及其他应用的可扩展互联网

• 批准号: 2201489
• 负责人: Scott Shenker
• 金额: $ 99.79万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2201489&HistoricalAwards=false
• 关键词: CC; Integration; Large; Extensible; Internet

Modern scientific research often involves huge datasets and many geographically distributed collaborators. The collaborative sharing of data in such research efforts requires rapid, flexible, and automated data transfers between sites. These sites have different computational and networking infrastructures, and are managed by different entities. To provide a uniform and extensible set of data sharing tools to such collaborations, the network should serve as a Data Valet for collaborating scientific institutions.This main technical challenge in achieving this goal lies not in each individual piece of data-sharing functionality. Rather, it lies in how one builds an extensible architecture where current data-handling features can synergistically coexist and new ones can be seamlessly incorporated. To meet this challenge, this effort will leverage a design called the Extensible Internet (EI). EI allows network operators to insert new data processing functionality in a way that (i) any host that is aware of the new functionality can use it and (ii) hosts that are unaware of the new functionality can continue to function. This system will be deployed on ESnet, which is a high-performance network optimized for large-scale science, interconnecting the National Laboratory System in the United States.The National Laboratory System pursues research in a wide array of fields. The work described here will facilitate any National Laboratory effort that involves the sharing of large datasets among geographically distributed collaborators. Potential opportunities for impact range from the biological sciences (e.g., genomic research) to the environmental sciences (e.g., climate research) to the physical sciences (e.g., Large Hadron Collider) to the energy sciences (e.g., National Synchrotron Light Source).This collaborative effort brings together researchers from Mount Holyoke College, New York University, the University of Washington, and the University of California at Berkeley. All source code, data, papers, documentation, and course materials produced as a part of the proposed work will be available from http://extensibleinternet.org/ . All material will remain available for at least five years after the end of this project or five years after publication, whichever is later. All source code will be released under a permissive license.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

现代科学研究通常涉及巨大的数据集和许多分布在不同地区的合作者。此类研究工作中的数据协作共享需要站点之间快速、灵活和自动化的数据传输。这些站点具有不同的计算和网络基础设施，并由不同的实体管理。为了向此类协作提供一套统一且可扩展​​的数据共享工具，网络应充当协作科学机构的数据代客。实现这一目标的主要技术挑战并不在于每个单独的数据共享功能。相反，它在于如何构建一个可扩展的架构，其中当前的数据处理功能可以协同共存，并且新的功能可以无缝合并。为了应对这一挑战，这项工作将利用一种称为可扩展互联网 (EI) 的设计。 EI 允许网络运营商以以下方式插入新的数据处理功能：(i) 任何知道新功能的主机都可以使用它，(ii) 不知道新功能的主机可以继续运行。该系统将部署在ESnet上，ESnet是一个针对大规模科学优化的高性能网络，与美国国家实验室系统互连。国家实验室系统在广泛的领域进行研究。这里描述的工作将促进任何涉及在地理分布的合作者之间共享大型数据集的国家实验室工作。潜在的影响机会范围从生物科学（例如基因组研究）到环境科学（例如气候研究）到物理科学（例如大型强子对撞机）到能源科学（例如国家同步加速器光源）。来自曼荷莲学院、纽约大学、华盛顿大学和加州大学伯克利分校的研究人员共同努力。作为拟议工作的一部分而制作的所有源代码、数据、论文、文档和课程材料都可以从 http://extensibleinternet.org/ 获取。所有材料将在本项目结束后至少五年内或出版后五年内（以较晚者为准）保留。所有源代码都将在许可下发布。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。