skip to main content
short-paper

On the efficiency of perfect simulation in monotone queueing networks

Authors Info & Claims
Published:15 September 2011Publication History
Skip Abstract Section

Abstract

We consider Jackson queueing networks (JQN) with finite capacity constraints and analyze the temporal computational complexity of sampling from their stationary distribution. In the context of perfect sampling, the monotonicity of JQNs ensures that it is the coupling time of extremal sample-paths. In the context of approximate sampling, it is given by the mixing time. We give a sufficient condition to prove that the coupling time of JQNs with M queues is O(MMi=1 Ci), where Ci denotes the capacity (buffer size) of queue i. This condition lets us deal with networks having arbitrary topology, for which the best bound known is exponential in the Ci's or in M. Then, we use this result to show that the mixing time of JQNs is log2 1/∈ O(MMi=1 Ci), where ∈ is a precision threshold. The main idea of our proof relies on a recursive formula on the coupling times of special sample-paths and provides a methodology for analyzing the coupling and mixing times of several monotone Markovian networks.

References

  1. S. Andradóttir and M. Hosseini-Nasab. Efficiency of time segmentation parallel simulation of finite markovian queueing networks. Operation Research, 51(2):272--280, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. G. Bolch, S. Greiner, H. de Meer, and K. Trivedi. Queueing Networks and Markov Chains. Wiley-Interscience, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. P. Bremaud. Markov Chains, Gibbs Fields, Monte Carlo Simulation and Queues. Texts in Applied Mathematics. Springer-Verlag, Berlin-Heidelberg, 1999.Google ScholarGoogle Scholar
  4. S. Kijima and T. Matsui. Approximation algorithm and perfect sampler for closed jackson networks with single servers. SIAM J. Comput., 38(4):1484--1503, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. A. Levin, Y. Peres, and E. L. Wilmer. Markov Chains and Mixing Times. American Math. Soc., 2008.Google ScholarGoogle ScholarCross RefCross Ref
  6. J. G. Propp and D. B. Wilson. Exact sampling with coupled markov chains and applications to statistical mechanics. Rand. Struct. Alg., 9(1-2):223--252, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. On the efficiency of perfect simulation in monotone queueing networks

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM SIGMETRICS Performance Evaluation Review
        ACM SIGMETRICS Performance Evaluation Review  Volume 39, Issue 2
        Special Issue on IFIP PERFORMANCE 2011- 29th International Symposium on Computer Performance, Modeling, Measurement and Evaluation
        September 2011
        75 pages
        ISSN:0163-5999
        DOI:10.1145/2034832
        Issue’s Table of Contents

        Copyright © 2011 Authors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 15 September 2011

        Check for updates

        Qualifiers

        • short-paper

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader