CC*DNI DIBBs: Give Your Data the Edge: A Scalable Data Delivery Platform

CC*DNI DIBB：为您的数据提供优势：可扩展的数据交付平台

• 批准号: 1541318
• 负责人: Larry Peterson
• 金额: $ 380.49万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541318&HistoricalAwards=false
• 关键词: CC; DNI; DIBBs; Give; Your

Scientific collaboration is increasingly data driven. Large volumes of data are generated, aggregated, archived, and shared?often with collaborators (and their compute resources) spread across the globe - with subsequent analysis generating still more data to archive and distribute. Scientists either become experts at data transfer, storage, and management, or their ability to build on each other?s work suffers. This project addresses this challenge, with an emphasis on easing the burden on the user, building a solution that is sustainable over the long term, and delivering performance that scales in the number of collaborators. The project's technical approach is to deploy a general-purpose storage platform, called Syndicate, that harnesses a collection of available storage components to provide a global, scalable, and secure storage service. These include public and private cloud storage (for data durability), network caches and content distribution networks (for scalable read bandwidth), and local disks (for local reads/write performance). The project's goal is to make it possible for applications to access data independent of where it is stored, where Syndicate simultaneously: (1) minimizes the operational burden imposed on users, (2) maximizes the use of commodity infrastructure; and (3) maximizes aggregate I/O performance. At its core, Syndicate's value proposition is to fully decouple storage semantics from infrastructure. This lets users select infrastructure based on its cost/performance trade-off, while ensuring that their domain-specific storage requirements are met. And to demonstrate this value, the project is building a pilot deployment that spans edge resources on nine campuses, and operating the capability on behalf of a diverse set of application domains, ranging from biology to network analytics to personalized medicine to retail and consumer analysis.

科学合作越来越受数据驱动。生成、聚合、归档和共享大量数据？通常协作者（及其计算资源）分布在地球仪上-随后的分析会生成更多的数据以进行归档和分发。科学家要么成为数据传输、存储和管理方面的专家，要么成为相互借鉴的能力专家？的工作受到影响。该项目解决了这一挑战，重点是减轻用户的负担，构建长期可持续的解决方案，并提供可扩展协作者数量的性能。 该项目的技术方法是部署一个名为Syndicate的通用存储平台，该平台利用一系列可用的存储组件来提供全球、可扩展和安全的存储服务。这些包括公共和私有云存储（用于数据持久性），网络缓存和内容分发网络（用于可扩展的读取带宽）以及本地磁盘（用于本地读取/写入性能）。该项目的目标是使应用程序能够独立于存储位置访问数据，其中Syndicate同时：（1）最大限度地减少对用户的操作负担，（2）最大限度地利用商品基础设施，以及（3）最大限度地提高聚合I/O性能。Syndicate的核心价值主张是将存储语义与基础设施完全分离。这使用户可以根据成本/性能权衡来选择基础架构，同时确保满足其特定于域的存储要求。为了证明这一价值，该项目正在构建一个跨越九个园区边缘资源的试点部署，并代表一系列不同的应用领域运行该功能，从生物学到网络分析，从个性化医疗到零售和消费者分析。