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

By Roy D. Yates, Sanjit Krishnan Kaul. IEEE Transactions on Information Theory, 2016

677 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Epidemiology

View Paper: https://www.semanticscholar.org/paper/9ef6f52374f3d071ba3e3a60e939b9e671062d04

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Citations in the corpus

Age of Information: An Introduction and Survey (2020, background): “multiple updating sources sharing a simple queue has proven challenging and there have been relatively few contributions [22], [66]–[69].”
Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications (2022, positive): “2) Age of Incorrect Information (AoII): While AoI is useful in characterizing the freshness of information and has found applications in a broad range of system settings under a variety of queuing disciplines [289]–[299], it does not explicitly take into account the similarity or discrepancy between”
Age of Information: A New Concept, Metric, and Tool (2018, background): “With ∗ is the minimum achievable age and with 4 the Nash equilibrium achieved by unilateral optimization [61].”
Optimal Status Update for Age of Information Minimization With an Energy Harvesting Source (2017, methodology): “The corresponding AoI has been analyzed in single-source singleserver queues [4], the M/M/1 Last-Come First-Served (LCFS) queue with preemption in service [5], the M/M/1 First-Come First-Served (FCFS) system with multiple sources [6], [7], and a multiple-source M/M/1 system which only keeps the late”