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Performance Analysis of A Queueing System with Server Arrival and Departure

Published:20 January 2022Publication History
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Abstract

In many systems, in order to fulfill demand (computing or other services) that varies over time, service capacities often change accordingly. In this paper, we analyze a simple two dimensional Markov chain model of a queueing system in which multiple servers can arrive to increase service capacity, and depart if a server has been idle for too long. It is well known that multi-dimensional Markov chains are in general difficult to analyze. Our focus is on an approximation method of stationary performance of the system via the Stein method. For this purpose, innovative methods are developed to estimate the moments of the Markov chain, as well as the solution to the Poisson equation with a partial differential operator.

References

  1. A. Bhandari, A. Scheller-Wolf, and M. Harchol-Balter. An exact and efficient algorithm for the constrained dynamic operator staffing problem for call centers. Management Science, 54(2):339--353, 2008.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. A. Braverman and J. G. Dai. Stein's method for steady-state diffusion approximations of m/Ph/n + m systems. Ann. Appl. Probab., 27(1):550--581, 02 2017.Google ScholarGoogle ScholarCross RefCross Ref
  3. M. J. Davis, Y. Lu, M. Sharma, M. Squillante, and B. Zhang. Stochastic optimization models for workforce planning, operations, and risk management. Service Science, 10(1):40--57, 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. G. Fayolle, R. Iasnogorodski, V. Malyshev, and V. Malyshev. Random Walks in the Quarter-Plane: Algebraic Methods, Boundary Value Problems and Applications. Applications of mathematics. Springer, 1999.Google ScholarGoogle Scholar
  5. I. Gurvich. Diffusion models and steady-state approximations for exponentially ergodic markovian queues. Ann. Appl. Probab., 24(6):2527--2559, 12 2014.Google ScholarGoogle ScholarCross RefCross Ref
  6. I. Gurvich. Validity of heavy-traffic steady-state approximations in multiclass queueing networks: The case of queue-ratio disciplines. Mathematics of Operations Research, 39(1):121--162, 2014.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. S. Halfin and W. Whitt. Heavy-Traffic Limits for Queues with Many Exponential Servers. Operations Research, 29(3):567--588, June 1981.Google ScholarGoogle Scholar
  8. N. Krylov and A. M. Society. Lectures on Elliptic and Parabolic Equations in Holder Spaces. Graduate studies in mathematics. American Mathematical Society, 1996.Google ScholarGoogle Scholar
  9. M. Lin, A. Wierman, L. L. H. Andrew, and E. Thereska. Dynamic right-sizing for power-proportional data centers. In 2011 Proceedings IEEE INFOCOM, pages 1098--1106, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  10. Y. Lu. On a two-dimensional markov chain model for performance analysis of systems with varying capacities. arXiv:2106.03145, 2021.Google ScholarGoogle Scholar
  11. Y. Lu, M. Sharma, M. S. Squillante, and B. Zhang. Stochastic optimal dynamic control of gim/gim/1n queues with time-varying workloads. Probability in the Engineering and Informational Sciences, 30(3):470--491, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  12. V. Mazalov and A. Gurtov. Queueing system with on-demand number of servers. Mathematica Applicanda, 40(2):1--12, 2012.Google ScholarGoogle Scholar
  13. R. Schollmeier. A definition of peer-to-peer networking for the classification of peer-to-peer architectures and applications. In Proceedings First International Conference on Peer-to-Peer Computing, pages 101--102, 2001.Google ScholarGoogle Scholar
  14. C. Stein. Approximate computation of expectations. Number 7. Institute of Mathematical Statistics Lecture Notes, Monograph Series, 1986.Google ScholarGoogle Scholar

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      • Published in

        cover image ACM SIGMETRICS Performance Evaluation Review
        ACM SIGMETRICS Performance Evaluation Review  Volume 49, Issue 2
        September 2021
        73 pages
        ISSN:0163-5999
        DOI:10.1145/3512798
        Issue’s Table of Contents

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        • Published: 20 January 2022

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