The Age of Information: Real-Time Status Updating by Multiple Sources

TLDR

The study examines multiple independent sources sending status updates to a monitor through simple queues. The authors formulate an age‑of‑information metric, derive a general result for multiple‑source service systems, and use it to characterize service sharing and develop a simplified evaluation technique. They employ stochastic hybrid systems to evaluate AoI, producing a simplified method whose complexity matches that of computing the stationary distribution of a finite‑state Markov chain. The work identifies the feasible region of average status ages for FCFS and two LCF queueing systems with Poisson arrivals and exponential service times.

Abstract

We examine multiple independent sources providing status updates to a monitor through simple queues. We formulate an age of information (AoI) timeliness metric and derive a general result for the AoI that is applicable to a wide variety of multiple source service systems. For first-come first-served and two types of last-come first-served systems with Poisson arrivals and exponential service times, we find the region of feasible average status ages for multiple updating sources. We then use these results to characterize how a service facility can be shared among multiple updating sources. A new simplified technique for evaluating the AoI in finite-state continuous-time queuing systems is also derived. Based on stochastic hybrid systems, this method makes AoI evaluation to be comparable in complexity to finding the stationary distribution of a finite-state Markov chain.