Cloud-to-Edge Computing: A Unified Computational Paradigm

云到边缘计算：统一计算范式

• 批准号: RGPIN-2019-06120
• 负责人: GasconSamson, Julien
• 金额: $ 1.68万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738723
• 关键词: Cloud; Edge; Computing; Unified; Computational

The Internet of Things (IoT) involves large amounts of interconnected devices that produce and consume data. Over the last few years, the IoT has gained tremendous popularity both in academia and many industry sectors. IoT devices can be found in many contexts, such as smart homes and smart buildings, intelligent vehicles, medical devices, the industry 4.0, etc. Gartner has estimated that there will be over 20 billion IoT devices by the year 2020. Historically, IoT devices consisted mostly of simple sensors and actuators that relayed data to/from the cloud with little to no local processing. Nowadays, IoT devices are getting more and more powerful and connected, and are quickly evolving beyond their traditional role of low-level embedded devices to become similar to embedded computers. For instance, the popular Raspberry Pi Zero W device features a 1 GHz CPU, 512 MB of RAM, WiFi and Bluetooth support, for only 5 USD. As these devices become more powerful, they can run full operating systems (e.g., Linux) and applications written in high-level, programmer-friendly languages (e.g., Java, JavaScript, Python), which opens the door to running more complex and higher-level applications and services directly on these devices (i.e., edge computing). My proposed research aims at providing a comprehensive model and a unified paradigm that will allow developers to write large-scale distributed high-level edge applications in a unified and interoperable manner, and to dynamically deploy these applications and the services that they consume (e.g., data storage, communications, file systems) close to where the data is produced, and directly onto the IoT devices themselves. I believe that this can yield several benefits, and can help alleviating the limitations of a purely centralized (i.e., cloud) model, such as reducing bandwidth and infrastructure costs; reducing latency, which can have an impact on real-time data processing and decision making; and alleviating the dependence on a central point of failure. The proposed research has the potential to explore and provide novel solutions to multi-dimensional challenges in a bleeding-edge field of research (cloud-edge computing). Research outcomes are expected through the form of publications to top-tier systems conferences (e.g., ICDCS, SEC, Middleware), in addition to contributing to the training of several (7) graduate students, which will learn important research and leadership skills that will make them valuable in thriving academic and industry markets. Benefits to the Canadian industry are envisioned, given that several key players are well established in the IoT landscape and in the telecom industry (e.g., Bell, Telus, Cisco, Intel), as well as benefits to Canada itself; e.g., a distributed deployment of applications and services could be beneficial in geographically dispersed communities and remote sites, and could ensure that sensitive data is processed locally, directly on trusted devices.

物联网（物联网）涉及大量生产和消耗数据的互连设备。在过去的几年中，物联网在学术界和许多行业领域都广受欢迎。物联网设备可以在许多情况下找到，例如智能房屋和智能建筑，智能车辆，医疗设备，行业4.0等。Gartner估计到2020年，Gartner估计将有超过200亿个物联网设备。主要由简单的传感器和执行器组成，这些传感器和执行器将数据传递到云中，几乎没有本地处理。如今，IoT设备变得越来越强大和连接，并且迅速发展远远超出了其低级嵌入式设备的传统作用，以与嵌入式计算机相似。例如，流行的Raspberry Pi Zero W设备仅提供1 GHz CPU，512 MB的RAM，WiFi和蓝牙支撑，仅提供5美元。随着这些设备变得越来越强大，它们可以运行完整的操作系统（例如Linux）和用高级，程序员友好的语言（例如Java，Java，JavaScript，Python）编写的应用 - 直接在这些设备上的应用程序和服务（即边缘计算）。我提出的研究旨在提供一个综合模型和统一的范式，该模型将使开发人员能够以统一和可互操作的方式编写大规模的分布式高级边缘应用程序，并动态部署这些应用程序及其消耗的服务（例如，例如，数据存储，通信，文件系统）靠近生成数据的位置，并直接在IoT设备本身上。我认为这可以带来一些好处，并可以帮助减轻纯粹的集中式（即云）模型的局限性，例如降低带宽和基础设施成本；减少潜伏期，这可能会对实时数据处理和决策产生影响；减轻对失败中心点的依赖。拟议的研究有潜力探索和提供新颖的解决方案，以解决流血的研究领域（云边缘计算）中的多维挑战。除了为培训几（7）个研究生的培训外，还将通过向顶级系统会议（例如ICDC，SEC，中间件）出版的出版物形式进行研究成果，这将学习重要的研究和领导能力使它们在蓬勃发展的学术和行业市场中很有价值。鉴于在物联网景观和电信行业（例如贝尔，泰勒斯，思科，英特尔）以及对加拿大本身的好处，对加拿大产业的好处是设想的。例如，应用程序和服务的分布式部署可能对地理分散的社区和远程站点有益，并可以确保直接在可信的设备上直接在本地处理敏感数据。