Design and Deployment of Interactive Petabyte Scale Applications

交互式 PB 级应用程序的设计和部署

• 批准号: RGPIN-2021-03721
• 负责人: Coady, Monica
• 金额: $ 2.55万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749792
• 关键词: Design; Deployment; Interactive; Petabyte; Scale

This proposed research program will establish fundamental properties for a platform designed to support a new class of applications in spatial computing. These data intensive applications must support highly collaborative environments with 3D emulation, manipulation and visualization of petabyte scale datasets in close to real-time. Comprehensive infrastructure for spatial computing has outstripped conventional computing platforms and requires integration not only with local and remote resources, but also must include peer--to--peer collaboration capability, and mixed reality interactive front-ends. This research will enable a new class of transformative applications that will offer unrivalled emulation experiences, deepening and diversifying the next generation of experts in any spatial domain. Small examples of this class of application have emerged, largely relying on local computing options with relatively small data sets. For example, medical practices are beginning to leverage advanced image processing and 3D technologies to create exact physical replicas of a patient's characteristics, allowing clinical teams to tailor care in unprecedented ways; environmental experts are beginning to fuse data from multiple sensors, satellites and other imagery to study local indications of climate change; and educational options are being enhanced through the creation of custom hands--on experiences for students using Augmented and Virtual Reality (AR/VR). But data sets are getting bigger------for example, new satellites will provide 20 TB of data per day. Currently however, there are no platforms for systematically deploying applications that capitalize on globally available, interdependent, petabyte scale data sets. Storage must be distributed, discoverable, and will require new open specifications that will evolve as the data sets continue to grow. The anticipated outcomes of this work will be threefold: (1) a methodology for building petabyte scale spatial computing applications based on a reference architecture derived from earth observation and remote sensing, (2) contributions to AI--assisted tool chains for development, deployment, emulation and monitoring of spatial applications, (3) design patterns of best practices for future applications incorporating tradeoffs in performance, scalability, availability and consistency. Students will work directly with stakeholders to evaluate the contributions of this proposed program, and our team will publish results for researchers and practitioners in both software engineering and systems. By targeting the fundamental tradeoffs at the platform level, this work will benefit researchers involved in any spatial computing domain. In terms of benefits on a national scale, we already working with stakeholders in the Data Commons projects within the Canadian Digital Supercluster.

这项拟议的研究计划将建立一个平台，旨在支持空间计算中的一类新的应用程序的基本属性。这些数据密集型应用程序必须支持高度协作的环境，具有接近实时的PB级数据集的3D仿真，操作和可视化。空间计算的综合基础设施已经超过了传统的计算平台，不仅需要与本地和远程资源集成，而且还必须包括对等协作能力和混合现实交互前端。这项研究将实现一类新的变革性应用，提供无与伦比的仿真体验，深化和多样化任何空间领域的下一代专家。这类应用的小例子已经出现，主要依赖于相对较小数据集的本地计算选项。例如，医疗实践开始利用先进的图像处理和3D技术来创建患者特征的精确物理复制品，使临床团队能够以前所未有的方式定制护理;环境专家开始融合来自多个传感器、卫星和其他图像的数据，以研究当地的气候变化迹象;通过为使用增强现实和虚拟现实（AR/VR）的学生创建定制的动手体验，教育选项正在得到增强。但数据集正在变得越来越大--例如，新的卫星每天将提供20 TB的数据。然而，目前还没有系统地部署应用程序的平台，这些应用程序可以利用全球可用的、相互依赖的PB级数据集。存储必须是分布式的、可扩展的，并且需要新的开放规范，这些规范将随着数据集的不断增长而发展。这项工作的预期成果将有三个方面：（1）基于来自地球观测和遥感的参考架构构建PB级空间计算应用的方法，（2）对AI辅助工具链的贡献，用于空间应用的开发，部署，仿真和监控，（3）未来应用的最佳实践设计模式，包括性能权衡，可扩展性、可用性和一致性。学生将直接与利益相关者合作，评估该计划的贡献，我们的团队将为软件工程和系统的研究人员和从业人员发布结果。通过在平台级别上进行基本的权衡，这项工作将使参与任何空间计算领域的研究人员受益。在全国范围内的利益方面，我们已经与加拿大数字超级集群内的数据共享项目的利益相关者合作。