A Probabilistic Approach to Growth Networks

Author:

Jelenković Predrag1,Kondev Jané2,Mohapatra Lishibanya3ORCID,Momčilović Petar4ORCID

Affiliation:

1. Department of Electrical Engineering, Columbia University, New York, New York 10027;

2. Martin A. Fisher School of Physics, Brandeis University, Waltham, Massachusetts 02453;

3. School of Physics and Astronomy, College of Science, Rochester Institute of Technology, Rochester, New York 14623;

4. Department of Industrial and Systems Engineering, Texas A&M University, College Station, Texas 77843

Abstract

Single-class closed queueing networks, consisting of infinite-server and single-server queues with exponential service times and probabilistic routing, admit product-from solutions. Such solutions, although seemingly tractable, are difficult to characterize explicitly for practically relevant problems due to the exponential combinatorial complexity of its normalization constant (partition function). In “A Probabilistic Approach to Growth Networks,” Jelenković, Kondev, Mohapatra, and Momčilović develop a novel methodology, based on a probabilistic representation of product-form solutions and large-deviations concentration inequalities, which identifies distinct operating regimes and yields explicit expressions for the marginal distributions of queue lengths. From a methodological perspective, a fundamental feature of the proposed approach is that it provides exact results for order-one probabilities, even though the analysis involves large-deviations rate functions, which characterize only vanishing probabilities on a logarithmic scale.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Management Science and Operations Research,Computer Science Applications

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