Matlab Code for the Distribution of Age of Information in Status Update Systems with Heterogeneous Information Sources

Aiming the analytical modeling of Age of Information (AoI) and Peak-AoI, uploaded codes construct and solve analytical models for Non-preemptive Bufferless, Probabilistic Generate-at-will (GAW) and Random Arrival with Single Buffer (RA-SB) servers using the theory of absorbing Markov Chains. In particular, they output per-source PAoI/AoI distributions in a setting with general number of sources where the sources may have different (i) general phase-type service time distributions, (ii) packet error probabilities and (iii) arrival rates. Towards the usage of analytical models, the script "numericalExample.m" provides an example which obtains per-source mean PAoI and AoI values as well as per-source PAoI and AoI violation probabilities for different servers.