Age of Loop for Wireless Networked Control Systems Optimization
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Abstract (arXiv)
Joint design of control and communication in Wireless Networked Control Systems (WNCS) is a promising approach for future wireless industrial applications. In this context, Age of Information (AoI) has been increasingly utilized as a metric that is more representative than latency in the context of systems with a sense-compute-actuate cycle. Nevertheless, AoI is commonly defined for a single communication direction, Downlink or Uplink, which does not capture the closed-loop dynamics. In this paper, we extend the concept of AoI by defining a new metric, Age of Loop (AoL), relevant for WNCS closed-loop systems. The AoL is defined as the time elapsed since the piece of information causing the latest action or state (depending on the selected time origin) was generated. We then use the proposed metric to learn the WNCS latency and freshness bounds and we apply such learning methodology to minimize the long term WNCS cost with the least amount of bandwidth. We show that, using the AoL, we can learn the control system requirement and use this information to optimize network resources.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Jun 2021.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 0; 2026: 1.
5 papers.
- 2023Optimization Theory Based Deep Reinforcement Learning for Resource Allocation in Ultra-Reliable Wireless Networked Control Systemscited by 3
- 2024Goal-oriented Communications based on Recursive Early Exit Neural Networkscited by 1
- 2024The Best Time for an Update: Risk-Sensitive Minimization of Age-Based Metricscited by 0
- 2024Semantic Communication and Control Co-Design for Multi-Objective Distinct Dynamicscited by 0
- 2026Beyond Freshness and Semantics: A Coupon-Collector Framework for Effective Status Updatescited by 0
- 2026Beyond Freshness and Semantics: A Coupon-Collector Framework for Effective Status Updates27 Mar 2026
- 2024Goal-oriented Communications based on Recursive Early Exit Neural Networks27 Dec 2024
- 2024Semantic Communication and Control Co-Design for Multi-Objective Distinct Dynamics3 Oct 2024
- 2024The Best Time for an Update: Risk-Sensitive Minimization of Age-Based Metrics3 Jan 2024
- 2023Optimization Theory Based Deep Reinforcement Learning for Resource Allocation in Ultra-Reliable Wireless Networked Control Systems28 Nov 2023