Stochastic Service Guarantee Analysis Based on Time-Domain Models

TL;DR

This paper introduces time-domain models for stochastic network calculus, providing probabilistic bounds on packet inter-arrival and service times, expanding the applicability of the theory to new network scenarios.

Contribution

It proposes novel time-domain traffic and server models based on probabilistic bounds, extending stochastic network calculus beyond traditional cumulative models.

Findings

Proves the five basic properties of the proposed time-domain models.

Demonstrates the models' applicability through examples.

Establishes broad applicability of the time-domain approach.

Abstract

Stochastic network calculus is a theory for stochastic service guarantee analysis of computer communication networks. In the current stochastic network calculus literature, its traffic and server models are typically based on the cumulative amount of traffic and cumulative amount of service respectively. However, there are network scenarios where the applicability of such models is limited, and hence new ways of modeling traffic and service are needed to address this limitation. This paper presents time-domain models and results for stochastic network calculus. Particularly, we define traffic models, which are based on probabilistic lower-bounds on cumulative packet inter-arrival time, and server models, which are based on probabilistic upper-bounds on cumulative packet service time. In addition, examples demonstrating the use of the proposed time-domain models are provided. On the basis of the proposed models, the five basic properties of stochastic network calculus are also proved, which implies broad applicability of the proposed time-domain approach.