Increasingly ubiquitous network connectivity has engendered applications in which sources send real-time updates of their status to interested recipients. Examples include position, velocity and acceleration updates from nearby cars that facilitate safe maneuvers in an intelligent transportation system; forest temperature and humidity updates that can help better predict and control forest fires; and status reports gathered from the human body that enable timely detection of bodily ailments. These applications need status updates to be as timely as possible despite limited network resources. This project explores new timeliness metrics as a basis for the evaluation and design of status update systems.
Starting from a time-average status-age measure that applies to a broad class of systems, this project analyzes queue-theoretic system abstractions consisting of a source, service facility and monitor. While initial conclusions have been based on queue-theoretic abstractions that are simpler than their real-world counterparts, the resulting insights are a useful starting point in understanding and designing systems that support real-time status updates. On this basis, the project goals include the design and evaluation of (1) distributed resource sharing algorithms for simple networks of competing status updaters, (2) multiple access protocols for status-updating wireless sensors sharing a random access channel, and (3) stochastic approximation algorithms for online optimization of status update systems operating in networks. An improved understanding of the analytic fundamentals of status updating will contribute to the development and ultimate deployment of efficient and timely status updating systems.
