Collaborative Research: PPoSS: Planning: S3-IoT: Design and Deployment of Scalable, Secure, and Smart Mission-Critical IoT Systems

协作研究：PPoSS：规划：S3-IoT：可扩展、安全和智能的关键任务物联网系统的设计和部署

• 批准号: 2028879
• 负责人: Danny Chen
• 金额: $ 3.27万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028879&HistoricalAwards=false
• 关键词: Collaborative; Research; PPoSS; Planning; S3

The growing capabilities of sensing, computing and communication devices are leading to an explosion of Internet of Things (IoT) infrastructures. In the meantime, advances in technologies such as autonomous systems and artificial intelligence promise enormous economic and societal benefits. Naturally, it is desirable to deploy these technologies in IoT infrastructures. However, such deployments present daunting changes for increasingly scaled-up IoT infrastructures in mission-critical applications such as medical, energy, transportation, and industrial-automation systems. These challenges stem from several major aspects in terms of scalability. First, the number of edge devices can be enormous, often in the order of billions, which makes centralized management infeasible. Second, there are multiple layers of heterogeneity. An IoT system can consist of heterogeneous computing subsystems; each subsystem can have heterogeneous computing devices; and each single device can be composed of different kinds of computing components. Third, mission-critical applications have stringent requirements in correctness, resilience, timeliness, security and safety. It is difficult for a large-scale IoT system to satisfy these requirements due to increasing opportunities for adversarial activity.To tackle these challenges, this project aims to develop a cross-layer and full hardware/software stack solution, referred to as the S3-IoT framework, for the design and deployment of scalable, secure, and smart mission-critical IoT systems. The S3-IoT framework will span three different computation layers, including data centers, gateways/aggregators, and edge devices, and cover four research foci, i.e., resource management, security and privacy, computer architecture/systems, and algorithms. In this planning project, an initial version of the S3-IoT framework will be developed. The S3-IoT framework will (i) leverage a layered structure - data centers, gateways/aggregators, and edge devices to accommodate the huge number of edge devices; (ii) develop cross-layer techniques to deal with the heterogeneity among these layers; and (iii) propose hardware and software co-design approaches that embrace the heterogeneity among computing components to improve the performance of all components within an individual layer. The S3-IoT framework will be evaluated by developing simulators with the layered structure as well as a small scale, comprehensive experimental testbed. The success of this planning project will lead to a convincing path to effective deployment of mission-critical IoT systems and infrastructures, particularly in terms of improving resilience to environmental uncertainties, system internal errors and faults, and malicious attacks.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.

传感、计算和通信设备功能的不断增强正在导致物联网 (IoT) 基础设施的爆炸式增长。与此同时，自主系统和人工智能等技术的进步有望带来巨大的经济和社会效益。当然，我们希望在物联网基础设施中部署这些技术。然而，此类部署给医疗、能源、交通和工业自动化系统等关键任务应用中日益扩大的物联网基础设施带来了巨大的变化。这些挑战源于可扩展性方面的几个主要方面。首先，边缘设备的数量可能非常巨大，通常达到数十亿数量级，这使得集中管理不可行。其次，存在多层异质性。物联网系统可以由异构计算子系统组成；每个子系统可以有异构计算设备；每个单一设备可以由不同种类的计算组件组成。第三，关键任务应用对正确性、弹性、及时性、安全性有严格的要求。由于对抗性活动的机会不断增加，大规模物联网系统很难满足这些要求。为了应对这些挑战，该项目旨在开发一种跨层、完整的硬件/软件堆栈解决方案，称为 S3-物联网框架，用于设计和部署可扩展、安全和智能的关键任务物联网系统。 S3-IoT框架将跨越三个不同的计算层，包括数据中心、网关/聚合器和边缘设备，并涵盖四个研究重点，即资源管理、安全和隐私、计算机架构/系统和算法。在这个规划项目中，将开发S3-IoT框架的初始版本。 S3-IoT 框架将 (i) 利用分层结构 - 数据中心、网关/聚合器和边缘设备来容纳大量边缘设备； (ii) 开发跨层技术来处理这些层之间的异质性； (iii) 提出硬件和软件协同设计方法，该方法包含计算组件之间的异构性，以提高单个层内所有组件的性能。 S3-IoT框架将通过开发具有分层结构的模拟器以及小规模的综合实验测试台来进行评估。该规划项目的成功将为有效部署任务关键型物联网系统和基础设施提供一条令人信服的道路，特别是在提高对环境不确定性、系统内部错误和故障以及恶意攻击的抵御能力方面。该奖项反映了 NSF 的法定使命通过使用基金会的智力价值和更广泛的影响审查标准进行评估，并被认为值得支持。

项目成果

Associative Memory Based Experience Replay for Deep Reinforcement Learning

• DOI: 10.1145/3508352.3549387
• 发表时间: 2022-07
• 期刊: 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD)
• 作者: Mengyuan Li;A. Kazemi;Ann Franchesca Laguna;Sharon Hu

HARP: Hierarchical Resource Partitioning in Dynamic Industrial Wireless Networks

• DOI: 10.1109/icdcs54860.2022.00103
• 发表时间: 2022-07
• 期刊: 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)
• 作者: Jiachen Wang;Tianyu Zhang;Dawei Shen;Xiao Hu;Song Han

APaS: An Adaptive Partition-Based Scheduling Framework for 6TiSCH Networks

APaS：6TiSCH 网络的自适应分区调度框架

• DOI: 10.1109/rtas52030.2021.00033
• 发表时间: 2021
• 期刊: the 27th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS
• 作者: Wang, Jiachen;Zhang, Tianyu;Shen, Dawei;Hu, Xiaobo Sharon;Han, Song
• 通讯作者: Han, Song

ODHD: one-class brain-inspired hyperdimensional computing for outlier detection

• DOI: 10.1145/3489517.3530395
• 发表时间: 2022-07
• 期刊: Proceedings of the 59th ACM/IEEE Design Automation Conference
• 作者: Ruixuan Wang;Xun Jiao;X. S. Hu

Distributed Successive Packet Scheduling for Multi-Channel Real-Time Wireless Networks

• DOI: 10.1109/rtcsa55878.2022.00014
• 发表时间: 2022-08
• 期刊: 2022 IEEE 28th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
• 作者: Dawei Shen;Tianyu Zhang;Jiachen Wang;Qingxu Deng;Song Han;X. Hu