First Name: 
Ege
Last Name: 
Gamgam

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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.

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The script "numericalExample.m" obtains per-source average AoI and per-source age violation probabilities for First Source First Serve (FSFS), Earliest Served First Serve (ESFS) and Single Buffer with Replacement (SBR) policies for N sources using analytical models based on Markov Fluid Queues (MFQ). It is also possible to obtain the exact per-source CDF using this script. To do so, only the input parameters of used functions, namely "FSFS.m", "ESFS.m" and "SBR.m", in this script should be modified accordingly.

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