Distribution of Age of Information in Status Update Systems With Heterogeneous Information Sources: An Absorbing Markov Chain-Based Approach
Nail Akar, Ege Orkun Gamgam
Abstract
In this letter, we obtain the exact distributions of the Age of Information (AoI) and Peak AoI (PAoI) in a non-preemptive multi-source status update system for (i) Generate-At-Will (GAW) servers with probabilistic transmissions (ii) Random Arrival with Single Buffer (RA-SB) servers employing probabilistic buffer management, using absorbing Continuous-Time Markov Chains (CTMC). For both servers, the information sources are allowed to have different relative urgencies, phase-type service time distributions, and transmission error probabilities, for the sake of generality. Numerical examples are presented to validate the proposed analytical model.
Topics & Concepts
ServerProbabilistic logicMarkov chainComputer scienceMarkov processProbability distributionTransmission (telecommunications)Statistical modelMarkov modelAlgorithmDistributed computingTheoretical computer scienceMathematical optimizationReal-time computingComputer networkMathematicsStatisticsTelecommunicationsArtificial intelligenceMachine learningAge of Information OptimizationCongenital Heart Disease StudiesAtomic and Subatomic Physics Research