Modeling Information Flow with a Multi-Stage Queuing Mode
Abstract
In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into stages, and information can flow from one stage to another. The model is formulated as a spatially-extended, continuous-time Markov chain where space represents different stages. This model is equivalent to a spatially-extended version of the M/M/s queue. The main modeling feature is the throttling function which describes the processor slowdown when the amount of information falls below a certain threshold. We derive the stationary distribution for this stochastic model and develop a closure for a deterministic ODE system that approximates the evolution of the mean and variance of the stochastic model. We demonstrate the validity of the closure with numerical simulations.
Cite
@article{arxiv.2308.02703,
title = {Modeling Information Flow with a Multi-Stage Queuing Mode},
author = {Mohammad Daneshvar and Richard C. Barnard and Cory Hauck and Ilya Timofeyev},
journal= {arXiv preprint arXiv:2308.02703},
year = {2024}
}