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A Heavy Traffic Theory of Two-Sided Queues

Authors:

Sushil Mahavir Varma,

Siva Theja MaguluriAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 49, Issue 3

Pages 43 - 44

https://doi.org/10.1145/3529113.3529127

Published: 25 March 2022 Publication History

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Abstract

Motivated by emerging applications in online matching platforms and marketplaces, we study a two-sided queue. Customers and servers that arrive into a two-sided queue depart as soon as they are matched.

References

[1]

D. Hurtado-Lange and S. T. Maguluri. Transform methods for heavy-traffic analysis. Stochastic Systems, 10(4):275--309, 2020.

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[2]

S. M. Varma and S. T. Maguluri. A heavy traffic theory of two-sided queues, 2021.

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Cited By

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Mahavir Varma S(2025)Stochastic Matching Networks: Theory and Applications to Matching PlatformsACM SIGMETRICS Performance Evaluation Review10.1145/3712170.371217352:3(3-6)Online publication date: 9-Jan-2025
https://dl.acm.org/doi/10.1145/3712170.3712173
Kohlenberg A(2024)Quality Versus Quantity in Dynamic Matching with Impatient AgentsSSRN Electronic Journal10.2139/ssrn.4804794Online publication date: 2024
https://doi.org/10.2139/ssrn.4804794
Kohlenberg AGurvich I(2024)The Cost of Impatience in Dynamic Matching: Scaling Laws and Operating RegimesManagement Science10.1287/mnsc.2023.01513Online publication date: 19-Jul-2024
https://doi.org/10.1287/mnsc.2023.01513
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A Heavy Traffic Theory of Two-Sided Queues
1. Mathematics of computing
  1. Probability and statistics
    1. Statistical paradigms

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cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 49, Issue 3

December 2021

77 pages

ISSN:0163-5999

DOI:10.1145/3529113

Editor:
Zhenhua Liu
Stony Brook University

Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 March 2022

Published in SIGMETRICS Volume 49, Issue 3

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Mahavir Varma S(2025)Stochastic Matching Networks: Theory and Applications to Matching PlatformsACM SIGMETRICS Performance Evaluation Review10.1145/3712170.371217352:3(3-6)Online publication date: 9-Jan-2025
https://dl.acm.org/doi/10.1145/3712170.3712173
Kohlenberg A(2024)Quality Versus Quantity in Dynamic Matching with Impatient AgentsSSRN Electronic Journal10.2139/ssrn.4804794Online publication date: 2024
https://doi.org/10.2139/ssrn.4804794
Kohlenberg AGurvich I(2024)The Cost of Impatience in Dynamic Matching: Scaling Laws and Operating RegimesManagement Science10.1287/mnsc.2023.01513Online publication date: 19-Jul-2024
https://doi.org/10.1287/mnsc.2023.01513
Kohlenberg AGurvich I(2023)The Cost of Impatience in Dynamic Matching: Scaling Laws and Operating RegimesSSRN Electronic Journal10.2139/ssrn.4453900Online publication date: 2023
https://doi.org/10.2139/ssrn.4453900
Panigrahi SGoswami VMund GBarik R(2023)Performance Evaluation of IoST–Mist–Fog–Cloud Framework for Geospatial Crime Data Visualization: A State Dependent Queueing ApproachSN Computer Science10.1007/s42979-023-02400-05:1Online publication date: 8-Dec-2023
https://dl.acm.org/doi/10.1007/s42979-023-02400-0

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Diffusion approximations for double-ended queues with reneging in heavy traffic

Heavy-traffic limits for nearly deterministic queues

Efficiency-Driven Heavy-Traffic Approximations for Many-Server Queues with Abandonments

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