The Diffusion Approximation for Tandem Queues in Heavy Traffic.

Abstract

Consider a pair of single server queues arranged in series. A limit theorem was proved to justify a heavy traffic approximation for the (two-dimensional) equilibrium waiting time distribution. Specifically the waiting time distribution was shown to be approximated by the limit distribution F of a certain vector stochastic process Z. The process Z was defined as an explicit, but relatively complicated, transformation of vector Brownian Motion, and the general problem of determining F was left unsolved. It is shown that Z is a diffusion process (continuous strong Markov process) whose state space S is the non-negative quadrant. On the interior of S, the process behaves as an ordinary vector Brownian Motion, and it reflects instantaneously at each boundary surface (axis). At one axis, the reflection is normal, but at the other axis it has a tangential component as well. The generator of Z is calculated. It is shown that the limit distribution F is the solution of a first passage problem for a certain dual diffusion process Z*. The generator of Z* is calculated, and the analytical theory of Markov process is used to derive a partial differential equation (with boundary conditions) for the density f of F. Necessary and sufficient conditions are found for f to be separable (for the limit distribution to have independent components).

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Document Details

Document Type
Technical Report
Publication Date
Aug 10, 1977
Accession Number
ADA044911

Entities

People

  • J. Michael Harrison

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Boundaries
  • Brownian Motion
  • Differential Equations
  • Diffusion
  • Equations
  • Fats
  • Fish
  • Generators
  • Markov Processes
  • Military Research
  • Operations Research
  • Partial Differential Equations
  • Photoacoustic Tomography
  • Random Variables
  • Reflection
  • Stochastic Processes
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Fluid Dynamics.
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Space
  • Space - Orbital Debris