This First Course in Stochastic Network Calculus builds on the lecture Performance Modeling of Distributed Systems at the University of Kaiserslautern. The concepts of stochastic network calclulus parallels those of deterministic network calculus. This is why I reference on the lecture of 2011 at several points to stress these connections. This document however is thought of a stand-alone course and hence a deep study of the lecture is not necessary (but recommended).
This course contains a rather large probability primer to ensure the student can really grasp the expressions, which appear in stochastic network calculus. A student familiar with probability theory might skip this first chapter and delve directly into the stochastic network calculus. For each topic exercises are given, which can (and should) be used to strengthen the understanding of the presented definitions and theory.