Absorbing Markov Chain-Based Analysis of Age of Information in Discrete-Time Dual-Queue Systems

Fuente: arXiv
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Main Authors: Feng, Yifan, Akar, Nail, Chen, Zhengchuan, Motani, Mehul
Format: Preprint
Published: 2025
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author Feng, Yifan
Akar, Nail
Chen, Zhengchuan
Motani, Mehul
author_facet Feng, Yifan
Akar, Nail
Chen, Zhengchuan
Motani, Mehul
contents Status update systems require the timely collection of sensing information for which deploying multiple sensors/servers to obtain diversity gains is considered as a promising solution. In this work, we construct an absorbing Markov chain (AMC) to exactly model Age of Information (AoI) in a discretetime dual-queue (DTDQ) status update system with generate at will (GAW) status updates, discrete phase-type (DPH-type) distributed service times and transmission freezing. Specifically, transmission is frozen for a certain number of slots following the initiation of a transmission, after which one of the two servers is allowed to simultaneously sample the monitored physical process and transmit a status update packet, according to the availabilities and priorities of the two servers. Based on the discrete-time AMC, we provide the exact distributions of both AoI and peak AoI (PAoI), enabling the derivation of arbitrary order moments. In addition, we analytically study the role of freezing using several typical service time distributions, including geometric, uniform, and triangular distributions. The introduction of freezing for DTDQ systems is demonstrated to be significantly beneficial in reducing the mean AoI for various service time distributions. Additionally, we study the impact of the statistical parameters of the service times and heterogeneity between the two servers on the freezing gain, i.e., reduction in mean AoI attained with optimum freezing policies.
format Preprint
id arxiv_https___arxiv_org_abs_2509_23360
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Absorbing Markov Chain-Based Analysis of Age of Information in Discrete-Time Dual-Queue Systems
Feng, Yifan
Akar, Nail
Chen, Zhengchuan
Motani, Mehul
Information Theory
Status update systems require the timely collection of sensing information for which deploying multiple sensors/servers to obtain diversity gains is considered as a promising solution. In this work, we construct an absorbing Markov chain (AMC) to exactly model Age of Information (AoI) in a discretetime dual-queue (DTDQ) status update system with generate at will (GAW) status updates, discrete phase-type (DPH-type) distributed service times and transmission freezing. Specifically, transmission is frozen for a certain number of slots following the initiation of a transmission, after which one of the two servers is allowed to simultaneously sample the monitored physical process and transmit a status update packet, according to the availabilities and priorities of the two servers. Based on the discrete-time AMC, we provide the exact distributions of both AoI and peak AoI (PAoI), enabling the derivation of arbitrary order moments. In addition, we analytically study the role of freezing using several typical service time distributions, including geometric, uniform, and triangular distributions. The introduction of freezing for DTDQ systems is demonstrated to be significantly beneficial in reducing the mean AoI for various service time distributions. Additionally, we study the impact of the statistical parameters of the service times and heterogeneity between the two servers on the freezing gain, i.e., reduction in mean AoI attained with optimum freezing policies.
title Absorbing Markov Chain-Based Analysis of Age of Information in Discrete-Time Dual-Queue Systems
topic Information Theory
url https://arxiv.org/abs/2509.23360