CAREER: Taming Wireless Devices Cross-Layer Errors with Assistive Networked Edges

职业：利用辅助网络边缘解决无线设备跨层错误

• 批准号: 2312738
• 负责人: Jianqing Liu
• 金额: $ 50万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2312738&HistoricalAwards=false
• 关键词: CAREER; Taming; Wireless; Devices; Cross

Wireless devices such as smart phones, computers and sensors are ubiquitous in our daily life and modern society, creating unprecedented benefits in work efficiency, healthcare, automation control and many more. Due to the imperfect electronics and noisy environments, wireless devices are inherently faculty which can result in multifaceted data errors in computing, caching, and communications (C3). These errors have been widely deemed harmful, so the state-of-the-art on error control mainly target for absolute error removal. Yet, data errors can be benign or even beneficial (e.g., introducing errors to gradients may help the machine learning models to escape local optima), while existing research that are reactive and non-functional fail to turn data errors into good. Hence, the research objective of this project is to proactively harvest, render, and control data errors across C3 of wireless devices for significant performance gains in energy efficiency, throughput, data privacy, etc. Moreover, the research efforts will be coupled with educational innovations through the development of new laboratories, lecture contents, outreach demos and a novel undergraduate/graduate co-learning pedagogy. The successful completion of this project will enhance diversity in the wireless workforce in the nation, promote community outreach and create fundamental innovations of wireless technologies that are transformative to future wireless applications (e.g., AI and smart health).The proposed research activities include a synergy of hardware and software designs across layers of application, embedded memory and front-end radio in wireless devices as well as network protocols on wireless network edges. Expected outcomes include: (1) Harvest and render errors to specific data bits (i.e., application-aware) at runtime to realize system performance gains. (2) Integrate and control errors with contextual awareness (e.g., channel condition) for optimized adaptation using implicit control signaling. (3) Develop a suite of edge networking protocols to facilitate control of erroneous data. In parallel efforts, the proposed education activities include the creation of hardware- and application-aware wireless projects, laboratories, lecture contents and outreach demos. These materials will be delivered holistically by following a designed undergraduate/graduate co-learning pedagogy and a planned undergraduate research pathway. Various outreach activities will be also designed and performed to target low-income and rural K-12 students and first-generation college students – unique under-represented groups at PI’s home state. Expected outcomes include: (1) Prepare K-12 students for future collegiate study by offering a clearer disciplinary focus. (2) Increase the diversity and the population of our nation’s workforce in wireless technologies.This project is jointly funded by the Division of Electrical, Communications and Cyber Systems, Directorate of Engineering, and the Established Program to Stimulate Competitive Research (EPSCoR).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.

智能手机、计算机和传感器等无线设备在我们的日常生活和现代社会中无处不在，在工作效率、医疗保健、自动化控制等方面创造了前所未有的好处。可能会导致计算、缓存和通信中的多方面数据错误（C3），这些错误被广泛认为是有害的，因此最先进的错误控制主要目标是绝对错误消除。良性或什至有益的（例如，向梯度引入误差可能有助于机器学习模型逃避局部最优），而现有的反应性和非功能性研究无法将数据误差转化为好的结果，因此，该项目的研究目标是主动收获。跨无线设备 C3 的数据错误呈现和控制，以显着提高能源效率、吞吐量、数据隐私等方面的性能。此外，研究工作将通过开发新实验室、讲座内容、外展演示与教育创新相结合和一个新颖的本科生/研究生该项目的成功完成将增强国家无线劳动力的多样性，促进社区外展并创造变革未来无线应用（例如人工智能和智能健康）的无线技术的基础创新。研究活动包括跨应用层、嵌入式存储器和无线设备中的前端无线电以及无线网络边缘的网络协议的硬件和软件设计的协同作用。预期成果包括：（1）收集错误并将其呈现给特定的数据位。 （即应用感知）在运行时实现系统性能增益 (2) 将错误与上下文感知（例如信道条件）集成并控制，以使用隐式控制信令进行优化适应。同时，拟议的教育活动包括创建硬件和应用感知的无线项目、实验室、讲座内容和外展演示，这些材料将按照设计的本科生/研究生整体提供。还将针对低收入和农村 K-12 学生以及第一代大学生（PI 所在州的独特弱势群体）设计和开展各种外展活动。包括：(1) 通过提供更明确的学科重点，为 K-12 学生未来的大学学习做好准备。(2) 增加我国无线技术劳动力的多样性和人口数量。该项目由电气部、通信和网络系统、工程理事会和刺激竞争研究既定计划 (EPSCoR)。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

项目成果

Privacy by Memory Design: Visions and Open Problems

内存设计的隐私：愿景和开放问题

• DOI: 10.1109/mm.2023.3337094
• 发表时间: 2024-01
• 期刊: IEEE Micro
• 影响因子: 3.6
• 作者: Liu, Jianqing;Gong, Na
• 通讯作者: Gong, Na

A Secure and Efficient Protocol for LoRa Using Cryptographic Hardware Accelerators

使用加密硬件加速器的 LoRa 安全高效协议

• DOI: 10.1109/jiot.2023.3304175
• 发表时间: 2023-12
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Puckett, Steven;Liu, Jianqing;Yoo, Seong;Morris, Thomas
• 通讯作者: Morris, Thomas

Neural layered min-sum decoders for cyclic codes

循环码的神经分层最小和解码器

• DOI: 10.1016/j.phycom.2023.102194
• 发表时间: 2023-12
• 期刊: Physical Communication
• 影响因子: 2.2
• 作者: Wang, Ming;Li, Yong;Liu, Jianqing;Guo, Taolin;Wu, Huihui;Lau, Francis C.M.
• 通讯作者: Lau, Francis C.M.

Towards Anonymous yet Accountable Authentication for Public Wi-Fi Hotspot Access with Permissionless Blockchains

通过无需许可的区块链实现公共 Wi-Fi 热点访问的匿名且负责任的身份验证

• DOI: 10.1109/tvt.2022.3218528
• 发表时间: 2023-03
• 期刊: IEEE Transactions on Vehicular Technology
• 影响因子: 6.8
• 作者: Niu, Yukun;Wei, Lingbo;Zhang, Chi;Liu, Jianqing;Fang, Yuguang
• 通讯作者: Fang, Yuguang