On the Model Transform in Stochastic Network Calculus

TL;DR

This paper investigates how transforming traffic and service models in stochastic network calculus affects performance bounds, providing practical guidance for model selection to balance analysis feasibility, usefulness, and computational ease.

Contribution

It offers an in-depth analysis of the impact of model transformations on performance bounds and guides model selection in stochastic network calculus.

Findings

Transformations influence the tightness of performance bounds.

Guidelines improve the practicality of stochastic network calculus.

Analysis balances between model complexity and computational feasibility.

Abstract

Stochastic network calculus requires special care in the search of proper stochastic traffic arrival models and stochastic service models. Tradeoff must be considered between the feasibility for the analysis of performance bounds, the usefulness of performance bounds, and the ease of their numerical calculation. In theory, transform between different traffic arrival models and transform between different service models are possible. Nevertheless, the impact of the model transform on performance bounds has not been thoroughly investigated. This paper is to investigate the effect of the model transform and to provide practical guidance in the model selection in stochastic network calculus.