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

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.