Age of Changed Information: Content-Aware Status Updating in the Internet of Things
Xijun Wang, Wenrui Lin, Chao Xu, Xinghua Sun, Xiang Chen

TL;DR
This paper introduces Age of Changed Information (AoCI), a content-aware metric for status freshness in IoT, and develops optimal updating policies considering both information age and content changes.
Contribution
It proposes AoCI as a new metric combining content change and age, and derives optimal policies using Markov decision processes for IoT status updates.
Findings
AoCI effectively captures content freshness alongside age.
Optimal policies are threshold-based in certain Markov process cases.
Simulation shows the proposed policy outperforms zero-wait baseline.
Abstract
In Internet of Things (IoT), the freshness of status updates is crucial for mission-critical applications. In this regard, it is suggested to quantify the freshness of updates by using Age of Information (AoI) from the receiver's perspective. Specifically, the AoI measures the freshness over time. However, the freshness in the content is neglected. In this paper, we introduce an age-based utility, named as Age of Changed Information (AoCI), which captures both the passage of time and the change of information content. By modeling the underlying physical process as a discrete time Markov chain, we investigate the AoCI in a time-slotted status update system, where a sensor samples the physical process and transmits the update packets to the destination. With the aim of minimizing the weighted sum of the AoCI and the update cost, we formulate an infinite horizon average cost Markov…
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Taxonomy
TopicsAge of Information Optimization · Congenital Heart Disease Studies · Cognitive Functions and Memory
