EO 3330 Network Calculus
Motivated by novel applications, over the last several years there is a renewed interest in the analysis of networked systems through queuing-theoretic means. This renewed interest comes from the goal of building low-latency (wireless) communication systems with high reliability guarantees. The corresponding delay analysis is done on the one-hand using Markov-chain techniques, while on the other hand using effective capacity and stochastic network calculus. Furthermore, taking estimation and closed-loop control applications into account, significant work has been done with respect to freshness analysis for networked systems using a novel metric called Age of Information (AoI). The analysis and optimization of AoI is perhaps one of the hottest theoretical directions in networked systems research today.
This course intends to introduce PhD students to the foundations and some of the applications of both these directions: delay as well as freshness analysis. The course covers three blocks: We first review deterministic, worst-case analysis of delay in networked systems, i.e. the theory of deterministic network calculus. We next cover stochastic delay analysis in networked systems, where we consider effective bandwidth/capacity analysis as well as stochastic network calculus. Finally, we turn to freshness analysis and optimization of networked systems, i.e. age-of-information analysis. In each block the emphasis is put on the relation of theory to practical problems in communication systems and networks. Hence, after covering the theory we show the applicability of the theoretical framework in each block to real problems. The course furthermore consists of homework assignments and a final project in which students work on after the course lectures have been completed. The projects are intended to relate to the research area of each PhD student, connecting it with the tools discussed in the course. Thus, the course targets at enabling PhD students to apply the introduced tools to the analysis of delay and freshness of networked systems.