CAREER: Towards Realizing Timely Information Transfer and Processing for Networked Communication Systems

With the ever-growing amounts of data exchanged in today's world, there needs to be a reliable means for timely information processing and transfer between the end users. Inspired by the novel age-of-information (AoI) metric that assesses information freshness, this proposal offers a pathway towards realizing the ex- change of data in a timely manner in federated learning (FL), cloud computing, and remote sensing systems. It introduces a novel information timeliness metric, AoI, into the study of these systems, and investigates various approaches to achieve timely learning, computing and sensing over networks. It has the potential to become an enabler for various applications, including collaborative autonomous driving, precision health- care, and others. As an integral part of this research proposal, an extensive educational plan that involves K-12, undergraduate and graduate level agendas is proposed.

This project spans three fundamental information processing categories. The first involves intelligent agents in a FL setup. Novel agent scheduling and efficient model compression algorithms are proposed for this category to realize the notion of timely FL at-scale. The second considers clients in cloud computing systems, for which innovative job uploading policies are devised under system-level constraints to achieve timely job completions. Finally, the third category focuses on remote sensing, and presents novel variable length coding schemes to enable timely multi-process tracking over noisy communication channels. This project has the potential to transform the way information acquisition and processing systems operate under stringent communication and resource constraints, while the educational plan provides the necessary tools to reason about the timeliness of information in networked systems.

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.