CIF: Small: Collaborative Research: On the Fundamental Nature of the Age of Updates

University Of Maryland, College Park, College Park MD

Investigators

Abstract

The Age of Information (AoI) has emerged as a novel concept, metric, and tool in the broad area of Information Sciences. AoI is clearly connected to many aspects of Information Theory, Signal Processing, and multiple applications. However, the fundamental nature of this concept has been elusive so far. This project will investigate all three aspects of the AoI, namely its significance as a performance metric, its usefulness as a tool, and, more importantly, its potential to explore profound aspects of, and fundamental interconnections among, the theories that underlie our understanding of information structure, causal information processing, and the context (or semanteme) of information. Especially in the latter, the context of the communication process is emerging as a well-defined and useful extension of the Shannon doctrine of communication. Namely, communication needs not be just reproducing at point B a message selected at point A. Rather, it is important to consider whether communication occurs for a purpose, such as for computation, prediction, or monitoring. Educational efforts will include course development at both undergraduate and graduate levels. The investigators will also strengthen the strong programs of their Institutions in recruiting women and under-represented minorities, as well as the involvement of undergraduate students in research. The proposed work aims at using the new concept of Age of Information to discover the relationships between Information Theory and Signal Processing, which are two of the main pillars of Information Science. Its foundational core is the context of communication, namely on the purposes and goals of signal transmission. This research will be carried out around three thrust areas: (i) the project will explore how the transmission and the age of received updates relate to the information structure of a signal, and understand how information ages over time; (ii) the project will use an innovative approach to the traditional problems of signal processing by relating Nyquist's theory to causal signal reconstruction; (iii) the project will use AoI as a tool in handling the problem of caching and network control in volatile environments (e.g., internet of things and sensor networks). 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.