PathFS: A File System for the Hierarchical Cloud

PathFS：分层云的文件系统

• 批准号: 577280-2022
• 负责人: deLara, EyalE
• 金额: $ 9.69万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 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=749982
• 关键词: PathFS; File; System; Hierarchical; Cloud

The advent of the Internet of Things (IoT) has led to a large amount of generated data, new requirements forreal-time processing, and the proliferation of distributed heterogeneous computing resources. In emergingscenarios, such as Smart Cities and Industry 4.0, files, videos, and pictures are produced by sensors on theedges of the Internet. Transporting this data over Internet links to cloud data centres for processing and storage places several bandwidth requirements on the network and is not compatible with applications that require low latency. Edge computing has emerged as an alternative approach that leverages small regional data centres, from a few computers to a few racks, at the Internet edges to carry out processing tasks and store data. This proximity to the location of data generation enables new systems that provide low latency and reduce network load.This proposal is a collaboration between the University of Toronto (UofT) and Konica Minolta Business Solutions (Canada) Ltd. . It aims to create PathFS, a new distributed file system (DFS) designed to be deployed over a hierarchy of data centres that span from the edge of the network for the wide-area cloud. PathFS is designed to support novel applications that can benefit from edge computing by providing low latency access to data and enabling local execution of data-intensive workloads. PathFS will simplify the development of edge applications by making it possible for distributed components to communicate with each other using a familiar file system interface. For example, a camera monitoring a factory's production line could store images of products to PathFS. A nearbyboard computer could then read the images to detect defects, using a light inference ML model. In turn, a morepowerful computer could perform factory-wide analytics by using PathFS to collect data from multipleproduction lines. Finally, a process running on a traditional wide-area cloud data centre could use PathFS toperform analytics using data collected from multiple factories.

物联网（IoT）的出现带来了大量的数据生成、对实时处理的新要求以及分布式异构计算资源的激增。在智能城市和工业4.0等新兴场景中，文件、视频和图片是由互联网边缘的传感器产生的。通过互联网链接将这些数据传输到云数据中心进行处理和存储，对网络提出了若干带宽要求，并且与需要低延迟的应用程序不兼容。边缘计算已经成为一种替代方法，它利用互联网边缘的小型区域数据中心（从几台计算机到几个机架）来执行处理任务和存储数据。这种接近数据生成位置的特性使得新系统能够提供低延迟并减少网络负载。该提案是多伦多大学（UofT）和柯尼卡美能达商业解决方案（加拿大）有限公司之间的合作。它旨在创建PathFS，这是一种新的分布式文件系统（DFS），旨在部署在从广域云网络边缘跨越的数据中心层次结构上。PathFS旨在通过提供对数据的低延迟访问并实现数据密集型工作负载的本地执行来支持可以从边缘计算中受益的新型应用程序。PathFS将简化边缘应用程序的开发，使分布式组件可以使用熟悉的文件系统接口相互通信。例如，监控工厂生产线的摄像头可以将产品图像存储到PathFS。然后，附近的计算机可以使用光推理ML模型读取图像以检测缺陷。反过来，更强大的计算机可以通过使用PathFS从多条生产线收集数据来执行工厂范围的分析。最后，在传统广域云数据中心上运行的流程可以使用PathFS使用从多个工厂收集的数据执行分析。