Analysis of Stochastic Service Guarantees in Communication Networks: A Basic Calculus

TL;DR

This paper develops a basic calculus for stochastic service guarantees in communication networks, introducing new definitions and results that extend deterministic network calculus to stochastic scenarios.

Contribution

It introduces the m.b.c stochastic arrival curve and stochastic service curve, generalizing deterministic concepts for stochastic network analysis.

Findings

Derived superposition and concatenation results for stochastic flows.

Characterized output, backlog, and delay guarantees under stochastic models.

Defined stochastic strict server for independent case analysis.

Abstract

A basic calculus is presented for stochastic service guarantee analysis in communication networks. Central to the calculus are two definitions, maximum-(virtual)-backlog-centric (m.b.c) stochastic arrival curve and stochastic service curve, which respectively generalize arrival curve and service curve in the deterministic network calculus framework. With m.b.c stochastic arrival curve and stochastic service curve, various basic results are derived under the (min, +) algebra for the general case analysis, which are crucial to the development of stochastic network calculus. These results include (i) superposition of flows, (ii) concatenation of servers, (iii) output characterization, (iv) per-flow service under aggregation, and (v) stochastic backlog and delay guarantees. In addition, to perform independent case analysis, stochastic strict server is defined, which uses an ideal service process and an impairment process to characterize a server. The concept of stochastic strict server not only allows us to improve the basic results (i) -- (v) under the independent case, but also provides a convenient way to find the stochastic service curve of a serve. Moreover, an approach is introduced to find the m.b.c stochastic arrival curve of a flow and the stochastic service curve of a server.