View in EDS

Approximate waiting times for queuing systems with variable cross-correlated arrival rates.

Saved in:
Bibliographic Details
Title: Approximate waiting times for queuing systems with variable cross-correlated arrival rates.
Authors: Bogachev, Mikhail I.1 (AUTHOR) rogex@yandex.com, Pyko, Nikita S.1 (AUTHOR), Tymchenko, Nikita1 (AUTHOR), Pyko, Svetlana A.1 (AUTHOR), Markelov, Oleg A.1 (AUTHOR)
Source: Physica A. Nov2024, Vol. 654, pN.PAG-N.PAG. 1p.
Subjects: Traffic flow, Queuing theory, Telecommunication traffic, Time-varying networks, Rainfall
Abstract: Modern information and telecommunication, transportation and logistic, economic and financial systems are represented by complex networks exhibiting traffic flows with spatio-temporal long-term persistence. Conventional queuing theory relies largely upon stationary models where traffic flows are assumed independent and are typically characterized by the first two moments of inter-arrival and service time distributions, leading to drastic underestimations of traffic flow delays. Here we extend a recent superstatistical approach focusing on traffic models with variable arrival rates by accounting for interdependent activity patterns on multiple network nodes. We suggest an analytical correction to the conventional stationary queue model given by the Kingman's formula based on the calculation of aggregated inter-arrival times variability from the variabilities of arrival rates at individual nodes and cross-correlations between them. We confirm our analytical approximations by comparing with computer simulation results and large-batch empirical traffic analysis from the backbone of a major academic network. We believe that our results, in combination with recent data on the effects of long-term temporal persistence in network traffic flow, are applicable to various complex networks not limited to information and telecommunication, transportation, and logistics but also to economics and finance, rainfall and river flow dynamics, water accumulation in reservoirs, and many other research domains exhibiting spatio-temporal interdependence patterns. • Abrupt bursts in traffic dynamics are governed by simultaneous multiple nodes access. • Inter-arrival times distribution is derived from cross-correlations between nodes. • Analytical correction for an approximate evaluation of waiting times is proposed. • Results are supported by computer simulations and large-batch traffic data analysis. • Corrections are applicable to complex networks governed by autonomous agents dynamics. [ABSTRACT FROM AUTHOR]
Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 180559634
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Approximate waiting times for queuing systems with variable cross-correlated arrival rates.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Bogachev%2C+Mikhail+I%2E%22">Bogachev, Mikhail I.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> rogex@yandex.com</i><br /><searchLink fieldCode="AR" term="%22Pyko%2C+Nikita+S%2E%22">Pyko, Nikita S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tymchenko%2C+Nikita%22">Tymchenko, Nikita</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pyko%2C+Svetlana+A%2E%22">Pyko, Svetlana A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Markelov%2C+Oleg+A%2E%22">Markelov, Oleg A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Physica+A%22">Physica A</searchLink>. Nov2024, Vol. 654, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Traffic+flow%22">Traffic flow</searchLink><br /><searchLink fieldCode="DE" term="%22Queuing+theory%22">Queuing theory</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication+traffic%22">Telecommunication traffic</searchLink><br /><searchLink fieldCode="DE" term="%22Time-varying+networks%22">Time-varying networks</searchLink><br /><searchLink fieldCode="DE" term="%22Rainfall%22">Rainfall</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Modern information and telecommunication, transportation and logistic, economic and financial systems are represented by complex networks exhibiting traffic flows with spatio-temporal long-term persistence. Conventional queuing theory relies largely upon stationary models where traffic flows are assumed independent and are typically characterized by the first two moments of inter-arrival and service time distributions, leading to drastic underestimations of traffic flow delays. Here we extend a recent superstatistical approach focusing on traffic models with variable arrival rates by accounting for interdependent activity patterns on multiple network nodes. We suggest an analytical correction to the conventional stationary queue model given by the Kingman's formula based on the calculation of aggregated inter-arrival times variability from the variabilities of arrival rates at individual nodes and cross-correlations between them. We confirm our analytical approximations by comparing with computer simulation results and large-batch empirical traffic analysis from the backbone of a major academic network. We believe that our results, in combination with recent data on the effects of long-term temporal persistence in network traffic flow, are applicable to various complex networks not limited to information and telecommunication, transportation, and logistics but also to economics and finance, rainfall and river flow dynamics, water accumulation in reservoirs, and many other research domains exhibiting spatio-temporal interdependence patterns. • Abrupt bursts in traffic dynamics are governed by simultaneous multiple nodes access. • Inter-arrival times distribution is derived from cross-correlations between nodes. • Analytical correction for an approximate evaluation of waiting times is proposed. • Results are supported by computer simulations and large-batch traffic data analysis. • Corrections are applicable to complex networks governed by autonomous agents dynamics. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=180559634
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.physa.2024.130152
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Traffic flow
        Type: general
      – SubjectFull: Queuing theory
        Type: general
      – SubjectFull: Telecommunication traffic
        Type: general
      – SubjectFull: Time-varying networks
        Type: general
      – SubjectFull: Rainfall
        Type: general
    Titles:
      – TitleFull: Approximate waiting times for queuing systems with variable cross-correlated arrival rates.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Bogachev, Mikhail I.
      – PersonEntity:
          Name:
            NameFull: Pyko, Nikita S.
      – PersonEntity:
          Name:
            NameFull: Tymchenko, Nikita
      – PersonEntity:
          Name:
            NameFull: Pyko, Svetlana A.
      – PersonEntity:
          Name:
            NameFull: Markelov, Oleg A.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 11
              Text: Nov2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 03784371
          Numbering:
            – Type: volume
              Value: 654
          Titles:
            – TitleFull: Physica A
              Type: main
ResultId 1