Age of Information-Aware Scheduling for Timely and Scalable Internet of Things Applications

We consider large scale Internet of Things applications requesting data from physical devices. We study the problem of timely dissemination of sensor data towards applications with freshness requirements by means of a cache. We aim to minimize direct access to the possibly battery powered physical devices, yet improving Age of Information as a data freshness metric. We propose an Age of Information-aware scheduling policy for the physical device to push sensor updates to the caches located in cloud data centers. Such policy groups application requests based on freshness thresholds, thereby reduces the number of requests and threshold misses, and accounts for delay variation. The policy is incrementally introduced as we study its behavior over ideal and more realistic communication links with delay variation. We numerically evaluate the proposed policy against a simple yet widely used periodic schedule. We show that our informed schedule outperforms the periodic schedule even under high delay variations.