Distribution of the peak age of information in a two-node transmission group modeled by a system with a group flow and a phase-type service time
- Authors: Matyushenko S.I.1, Samouylov K.E.1
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Affiliations:
- RUDN University
- Issue: Vol 32, No 3 (2024)
- Pages: 260-270
- Section: Computer Science
- URL: https://journals.rcsi.science/2658-4670/article/view/315398
- DOI: https://doi.org/10.22363/2658-4670-2024-32-3-260-270
- EDN: https://elibrary.ru/EUVTRK
- ID: 315398
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Abstract
This article continues the cycle of works by the authors devoted to the problem of the age of information (AoI), a metric used in information systems for monitoring and managing remote sources of information from the control center. The theoretical analysis of information transmission systems requires a quantitative assessment of the “freshness” of information delivered to the control center. The process of transferring information from peripheral sources to the center is usually modeled using queuing systems. In this paper, a queuing system with phase-type distributions is used to estimate the maximum value of the information age, called the peak age. This takes into account the special requirement of the transmission protocol, which consists in the fact that information enters the system in groups of random size. For this case, an expression is obtained for the Laplace-Stieltjes transformation of the stationary distribution function of the peak age of information and its average value. Based on the results of analytical modeling, a numerical study of the dependence of the average value of the peak age of information on the system load was carried out. The correctness of the expressions obtained was verified by comparing the analytical results with the results of simulation modeling.
About the authors
Sergey I. Matyushenko
RUDN University
Email: matyushenko-si@rudn.ru
ORCID iD: 0000-0001-8247-8988
Candidate of Physical and Mathematical Sciences, Assistant professor of Department of Probability Theory and Cyber Security
6 Miklukho-Maklaya St, Moscow, 117198, Russian FederationKonstantin E. Samouylov
RUDN University
Author for correspondence.
Email: samuylov-ke@rudn.ru
ORCID iD: 0000-0002-6368-9680
Professor, Doctor of Technical Sciences, Head of the Department of Probability Theory and Cyber Security
6 Miklukho-Maklaya St, Moscow, 117198, Russian FederationReferences
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