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; however, 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 this recent work has been directed toward an analytic understanding of AoI using mathematical models. While the analysis of basic models and methods needs to continue, the merits of AoI also need to be studied in the context of specific applications. Thus, this project has four components: (1) State Dependent Updating: the update submission process will be optimized for a source that is subject to energy and power constraints in sending updates through a time-varying service facility. (2) Status Update Multiple Access: new protocols will be designed for wireless sensors sending updates through a shared random access channel. (3) Real-time Universal Data Compression: for a discrete random source with unknown statistics, the AoI performance of universal streaming source coding systems will be characterized. (4) Remote Video Updating: the AoI metric will be used to study how H.264 video frames should be delivered for machine-based surveillance. The first three project components will aim for new mathematical insights, methods and algorithms in fundamental problem areas. The fourth component, video updating, represents an application area to which these methods and algorithms will be applied.
|Effective start/end date||7/1/17 → 6/30/20|
- National Science Foundation (National Science Foundation (NSF))