This thesis investigates how to optimally monitor and estimate real-time information from remote systems when communication resources are limited or delayed. In modern networked systems—such as sensor networks, autonomous agents, or industrial control applications—measurements often traverse unreliable or congested channels before reaching a central estimator. This raises a fundamental question: When should data be sampled and transmitted to ensure accurate and timely understanding of the system state?

The thesis will explore strategies that balance the freshness of information (often quantified by metrics like the Age of Information) with the quality of estimation. It will involve studying optimal sampling policies, understanding the impact of transmission delays, and characterizing how these factors affect overall system performance. The student will engage with both theoretical models and simulation tools to gain insights relevant to real-world applications in remote monitoring, edge computing, and cyber-physical systems.

Voraussetzungen

In this seminar, we will examine communication-efficient policies tailored to the unique demands of IoT applications. Rather than focusing solely on maximizing throughput, we will explore how messages contribute to overarching objectives—such as monitoring system status or controlling physical processes—and balance these factors to prevent undue network congestion. Over the course of the seminar, students will gain a deeper understanding of relevant modeling approaches, design considerations, and performance trade-offs. Depending on the student’s interests and background, the seminar can be oriented toward methods grounded in reinforcement learning or dynamic programming to devise and analyze these communication-efficient strategies.

Inspired by the framework of real-time tracking under imperfect forward and feedback channels (as discussed in [arXiv:2407.06749v2]), we will examine how to minimize a time-averaged distortion (or estimation error) while respecting energy constraints. The overarching theme is deciding “when” and “how” to send status updates so that network congestion is avoided and physical processes are accurately tracked, despite error-prone acknowledgments and partial knowledge at the transmitter.

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Voraussetzungen