Age of Loop for Wireless Networked Control Systems Optimization

TL;DR

This paper introduces the Age of Loop (AoL), a new metric for Wireless Networked Control Systems that captures the closed-loop dynamics better than traditional Age of Information, enabling optimized resource allocation.

Contribution

The paper proposes AoL as an extension of AoI for closed-loop systems, and demonstrates its use in learning system requirements to optimize network bandwidth and control.

Findings

AoL effectively captures closed-loop dynamics in WNCS.

Using AoL, the system can learn latency and freshness bounds.

AoL-based optimization reduces long-term WNCS costs.

Abstract

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.