EAGER: Exploring intelligent services for managing uncertainty under constraints across the Computing Continuum: A case study using the SAGE platform

EAGER：探索在整个计算连续体的约束下管理不确定性的智能服务：使用 SAGE 平台的案例研究

• 批准号: 2238064
• 负责人: Manish Parashar
• 金额: $ 30万
• 依托单位: University of Utah
• 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: 2022-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238064&HistoricalAwards=false
• 关键词: EAGER; Exploring; intelligent; services; managing

Advanced cyberinfrastructures seek to make streaming data a modality for the scientific community by offering rich sensing capabilities across the edge-to-Cloud Computing Continuum. For societal applications based on multiple geo-distributed data sources and sophisticated data analytics, such as wildfire detection or personal safety, these platforms can be incredibly transformative. However, it is challenging to match user constraints (response time, quality, energy) with what is feasible in a heterogeneous and dynamic computation environment coupled with uncertainty in the availability of data. Identifying events and accelerating responses critically depends on the capacity to select resources and configure services under uncertain operating conditions. This project develops software abstractions that react at runtime to unforeseen events, and adaptation of the resources and computing paths between the edge and the cloud. This research is driven by the unique capabilities of the SAGE cyberinfrastructure as a case study to explore data-driven reactive behaviors at the network's edge on a national scale. The project proposes intelligent services to drive computing optimization from urgent scenarios on large cyberinfrastructures. The project focuses on resource management and programming support around three interrelated tasks: (1) developing models for capturing the dynamics of edge resources; (2) researching software abstractions for reactive analytics; and (3) addressing cost/benefit tradeoffs to drive the autonomous reconfiguration of applications and resources under constraints. The outcomes are intended to directly extend the SAGE platform and provide artifacts for creating urgent analytics, which will benefit SAGE users and the scientific community.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.

高级网络基础设施试图通过在边缘到云计算连续体中提供丰富的传感能力来使流媒体数据成为科学界的方式。对于基于多个地理分布的数据源和复杂数据分析（例如野火检测或人身安全）的社会应用程序，这些平台可能具有令人难以置信的变革性。但是，将用户限制（响应时间，质量，能量）与在异质和动态计算环境中可行的匹配以及数据的可行性以及数据可用性的不确定性相匹配，这是一项挑战。识别事件和加速响应严重取决于在不确定的操作条件下选择资源和配置服务的能力。该项目开发了软件摘要，这些摘要在运行时做出反应，以不可预见的事件，并适应边缘和云之间的资源和计算路径。这项研究是由Sage Cyber​​infrstructure的独特功能驱动的，作为案例研究，以探索国家范围内网络边缘的数据驱动的反应性行为。该项目提出了智能服务，以从大型网络基础结构的紧急情况下推动计算优化。 该项目着重于三个相互关联的任务的资源管理和编程支持：（1）开发用于捕获边缘资源动态的模型； （2）研究用于反应性分析的软件摘要； （3）解决成本/福利折衷方案，以推动在约束下的应用程序和资源的自主重新配置。结果旨在直接扩展SAGE平台，并为创建紧急分析提供工件，这将使Sage用户和科学界受益。该奖项反映了NSF的法定任务，并认为值得通过基金会的知识分子的智力优点和更广泛的影响来通过评估来进行支持。