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NSF-BSF: FET: Small: Redundancy for Storage in the Edge

NSF-BSF：FET：小型：边缘存储的冗余

基本信息

批准号：
2120262
负责人：
Emina Soljanin
金额：
$ 50万
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：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2025-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120262&HistoricalAwards=false
关键词：
NSF BSF FET Small Redundancy

项目摘要

The IoT revolution is driven by a surge of applications based on intelligent edge devices, such as smart cities and homes, autonomous vehicles, online video gaming, virtual and augmented reality, and machine learning. The edge devices generate large amounts of data and are the end-point executing user-facing applications. The back-end of these systems is a central service where data is continuously collected, aggregated, and analyzed, and a significant part of the logic is executed. Unfortunately, traditional cloud services cannot provide performance guarantees that these latency-critical applications require, mainly due to round-trip times which can take several hundreds of milliseconds. Thus, such applications will likely rely on Edge services--an emerging technology tightly coupled with 5G cellular networks. Edge solutions are envisioned to provide storage and compute infrastructure at interoperating edge nodes located at geographical locations near the users, such as the base of cellular network towers. This project focuses on enabling unstable edge nodes to collectively provide a reliable storage service for unpredictable user demands. Towards this goal, redundant storage schemes for edge systems will be designed and evaluated. The schemes will then be implemented and validated in a system-level platform that combines a physical test-bed and large-scale simulations. The project's primary goal is to characterize the schemes' system-level costs and benefits and leverage this understanding to design an edge service that will be readily applicable to real settings. This research amalgamates system-level design and optimization with mathematical analysis and thus will stimulate students' interest in both practice and theory associated with modern computing environments. In addition, this research will help improve the efficiency and robustness of edge computing, thus avoiding routing traffic to data centers. Such Edge services will reduce energy consumption, alleviate some of the load on the Internet backbone, and thus accelerate the development and adaptation of critical IoT applications.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.

物联网革命是由基于智能边缘设备的应用激增推动的，例如智能城市和家庭、自动驾驶汽车、在线视频游戏、虚拟和增强现实以及机器学习。边缘设备生成大量数据，是执行面向用户应用程序的端点。这些系统的后端是一个中心服务，数据在其中被持续地收集、聚合和分析，并执行重要的逻辑部分。不幸的是，传统的云服务无法提供这些延迟关键型应用程序所需的性能保证，这主要是由于往返时间可能需要数百毫秒。因此，这些应用可能依赖于边缘服务——一种与5G蜂窝网络紧密结合的新兴技术。边缘解决方案被设想为在位于用户附近地理位置的互操作边缘节点上提供存储和计算基础设施，例如蜂窝网络塔的基础。这个项目的重点是使不稳定的边缘节点能够共同为不可预测的用户需求提供可靠的存储服务。为了实现这一目标，将设计和评估边缘系统的冗余存储方案。然后，这些方案将在一个结合了物理试验台和大规模模拟的系统级平台上实施和验证。该项目的主要目标是描述方案的系统级成本和收益，并利用这种理解来设计易于应用于实际环境的边缘服务。本研究将系统级设计和优化与数学分析相结合，从而激发学生对与现代计算环境相关的实践和理论的兴趣。此外，本研究将有助于提高边缘计算的效率和鲁棒性，从而避免将流量路由到数据中心。这种边缘服务将降低能耗，减轻互联网骨干网的部分负载，从而加速关键物联网应用的开发和适应。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。