Collaborative Research: Streaming and Steering Applications: Requirements and Infrastructure (October 1-3, 2015)

合作研究：流媒体和转向应用：要求和基础设施（2015 年 10 月 1-3 日）

• 批准号: 1549516
• 负责人: Shantenu Jha
• 金额: $ 0.25万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1549516&HistoricalAwards=false
• 关键词: Collaborative; Research; Streaming; Steering; Applications

In association with the "big data" phenomena with greater volumes of data being generated, there has been an increase in the need to analyze and process that data in real-time. Example sources of this data include social media, robots, scientific instruments and simulations. Real-time analysis of "big data" holds great promise for industry, finance, communication, first responders, and public safety, to name just a few promising areas. Common to these applications is the requirement to process, analyze and respond to data immediately to make "live" decisions and steer applications. This project will organize and hold a workshop that will lay the foundations for a common understanding of the requirements and help the scientific community prepare for data of ever greater volumes and acquisition velocity. This project will support a community workshop to understand the class of applications that entail streaming data and related (near) real-time steering and control. Such applications are increasing in their sophistication, pervasiveness and scale. The goal of the workshop is to identify application, infrastructure and technology communities in this area and to clarify challenges that they face. Workshop participants will focus on application features and requirements as well as hardware and software needed to support them and will identify recommendations for NSF's production distributed cyberinfrastructure (hardware and software) for both the short and long term.

与产生更大量数据的“大数据”现象相关联，对实时分析和处理这些数据的需求有所增加。这些数据的示例来源包括社交媒体、机器人、科学仪器和模拟。“大数据”的实时分析为工业、金融、通信、急救人员和公共安全等领域带来了巨大的希望。这些应用程序的共同点是需要立即处理、分析和响应数据，以做出“实时”决策并引导应用程序。该项目将组织和举办一次讲习班，为共同理解各项要求奠定基础，并帮助科学界为数量和获取速度越来越大的数据做好准备。该项目将支持一个社区研讨会，以了解需要流数据和相关（近）实时转向和控制的应用程序的类别。这些应用的复杂性、普遍性和规模都在增加。研讨会的目标是确定这一领域的应用程序、基础设施和技术社区，并澄清他们面临的挑战。研讨会参与者将重点关注应用程序的功能和要求以及支持它们所需的硬件和软件，并将确定NSF生产分布式网络基础设施（硬件和软件）的短期和长期建议。