Modeling and Analysis of Queuing Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 2157

Special Issue Editor


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Guest Editor
Institute of Applied Mathematics and Computer Science, National Research Tomsk State University, Tomsk 634050, Russia
Interests: queueing systems; mathematical modeling; applied mathematics

Special Issue Information

Dear Colleagues,

We would like to invite you to submit your papers to the Special Issue, "Modeling and Analysis of Queuing Systems".

In this Special Issue, we propose to collect articles devoted to recent studies in the field of Queuing Theory. These can be works related to technology, social or economic problems, or problems in any other areas. We also invite publications and papers in the field of pure queueing theory, as these can serve as a basis for future applied research.

Prof. Dr. Svetlana Moiseeva
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • queuing theory
  • networks
  • telecommunications
  • control and reliability in queues
  • stochastic modeling
  • applied probability
  • matrix analytic methods
  • asymptotic analysis of queuing models

Published Papers (2 papers)

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Research

20 pages, 847 KiB  
Article
Queuing Model with Customer Class Movement across Server Groups for Analyzing Virtual Machine Migration in Cloud Computing
by Anna Kushchazli, Anastasia Safargalieva, Irina Kochetkova and Andrey Gorshenin
Mathematics 2024, 12(3), 468; https://doi.org/10.3390/math12030468 - 1 Feb 2024
Viewed by 907
Abstract
The advancement of cloud computing technologies has positioned virtual machine (VM) migration as a critical area of research, essential for optimizing resource management, bolstering fault tolerance, and ensuring uninterrupted service delivery. This paper offers an exhaustive analysis of VM migration processes within cloud [...] Read more.
The advancement of cloud computing technologies has positioned virtual machine (VM) migration as a critical area of research, essential for optimizing resource management, bolstering fault tolerance, and ensuring uninterrupted service delivery. This paper offers an exhaustive analysis of VM migration processes within cloud infrastructures, examining various migration types, server load assessment methods, VM selection strategies, ideal migration timing, and target server determination criteria. We introduce a queuing theory-based model to scrutinize VM migration dynamics between servers in a cloud environment. By reinterpreting resource-centric migration mechanisms into a task-processing paradigm, we accommodate the stochastic nature of resource demands, characterized by random task arrivals and variable processing times. The model is specifically tailored to scenarios with two servers and three VMs. Through numerical examples, we elucidate several performance metrics: task blocking probability, average tasks processed by VMs, and average tasks managed by servers. Additionally, we examine the influence of task arrival rates and average task duration on these performance measures. Full article
(This article belongs to the Special Issue Modeling and Analysis of Queuing Systems)
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10 pages, 528 KiB  
Article
Asymptotic Diffusion Method for Retrial Queues with State-Dependent Service Rate
by Anatoly Nazarov, Ekaterina Fedorova, Olga Lizyura and Radmir Salimzyanov
Mathematics 2023, 11(14), 3140; https://doi.org/10.3390/math11143140 - 16 Jul 2023
Viewed by 681
Abstract
In this paper, we consider a retrial queue with a state-dependent service rate as a mathematical model of a node of FANET communications. We suppose that the arrival process is Poisson, the delay duration is exponentially distributed, the orbit is unlimited, and there [...] Read more.
In this paper, we consider a retrial queue with a state-dependent service rate as a mathematical model of a node of FANET communications. We suppose that the arrival process is Poisson, the delay duration is exponentially distributed, the orbit is unlimited, and there is multiple random access from the orbit. There is one server, and the service time of every call is distributed exponentially with a variable parameter depending on the number of calls in the orbit. The service rate has an infinite number of values. We propose the asymptotic diffusion method for the model study. The asymptotic diffusion approximation of the probability distribution of the number of calls in the orbit is derived. Some numerical examples are demonstrated. Full article
(This article belongs to the Special Issue Modeling and Analysis of Queuing Systems)
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