With the emergence of cyber-physical systems, real-time status updates have become an important and ubiquitous form of communication. Applications that employ vehicular status messages, security reports from computers, homes, and offices, and surveillance video from remote-controlled systems need status updates to be as timely as possible but this is typically constrained by limited network resources.
This tension has led to the introduction of new performance metrics based on the Age of Information (AoI) that capture how timely is one’s knowledge of a system or process. AoI-based optimization of both the network service facility and the senders’ updating policies has yielded new and even surprising results that ultimately will increase the reliability of vehicular safety warning systems, reduce the bandwidth needed for video monitoring, and increase the energy efficiency of sensor networks.
Much of the recent work on AoI has been directed toward an analytic understanding of AoI using mathematical models. While the analysis of basic models and methods has continued, the merits of AoI also need to be studied in the context of specific applications:
In Fall 2018, this Timely Updating project was the basis for the ECE 559 Advanced Topics in Communication course on Age of Information. In this graduate course, which included three women students, the underlying material was traditional stochastic processes (renewal processes, Markov chains, queueing theory, limits of time averages, etc.) but the driving applications were AoI-based. The students seemed to enjoy seeing traditional topics through the lens of AoI. Course project topics included ”AoI in broadcast systems with energy harvesting sources”, ”Age analysis of CSMA”, ”Age in depth-based routing for underwater sensor networks.” As instructor, I received useful feedback on teaching the Stochastic Hybrid Systems (SHS) approach to AoI calculation.
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