# Age of Information with Gilbert-Elliot Servers and Samplers

arXiv: https://arxiv.org/abs/2002.05711 · HTML: https://mlsanity.com/paper/2002.05711/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Gradient Coding with Dynamic Clustering for Straggler-Tolerant Distributed Learning](https://mlsanity.com/paper/2103.01206/) (2021)

## Abstract (arXiv)

We study age of information in a status updating system that consists of a single sampler, i.e., source node, that sends time-sensitive status updates to a single monitor node through a server node. We first consider a Gilbert-Elliot service profile at the server node. In this model, service times at the server node follow a finite state Markov chain with two states: bad state b and good state g where the server is faster in state g. We determine the time average age experienced by the monitor node and characterize the age-optimal state transition matrix P with and without an average cost constraint on the service operation. Next, we consider a Gilbert-Elliot sampling profile at the source. In this model, the interarrival times follow a finite state Markov chain with two states: bad state b and good state g where samples are more frequent in state g. We find the time average age experienced by the monitor node and characterize the age-optimal state transition matrix P.