Age- and Deviation-of-Information of Time-Triggered and Event-Triggered Systems

TL;DR

This paper compares age-of-information and deviation-of-information metrics in time-triggered and event-triggered systems, showing that event-triggered systems can match time-triggered performance with less network usage.

Contribution

It introduces a deviation-of-information metric and demonstrates that event-triggered systems can achieve comparable information freshness with lower network utilization.

Findings

Event-triggered systems can perform as well as time-triggered systems in information freshness.

Event-triggered systems cause smaller mean network utilization.

Deviation-of-information is a useful signal-aware metric for system performance.

Abstract

Age-of-information is a metric that quantifies the freshness of information obtained by sampling a remote sensor. In signal-agnostic sampling, sensor updates are triggered at certain times without being conditioned on the actual sensor signal. Optimal update policies have been researched and it is accepted that periodic updates achieve smaller age-of-information than random updates. We contribute a study of a signal-aware policy, where updates are triggered by a random sensor event. By definition, this implies random updates and as a consequence inferior age-of-information. Considering a notion of deviation-of-information as a signal-aware metric, our results show, however, that event-triggered systems can perform equally well as time-triggered systems while causing smaller mean network utilization.