DNC

Deterministic Network Calculus (DNC) [Winter 2024]

Distributed systems are omnipresent nowadays and networking them is fundamental for the continuous dissemination and thus availability of data. Provision of data in real-time is one of the most important non-functional aspects that safety-critical networks must guarantee. Formal verification of data communication against worst-case deadline requirements is key to certification of emerging x-by-wire systems. Verification allows aircraft to take off, cars to steer by wire, and safety-critical industrial facilities to operate. Therefore, different methodologies for worst-case modeling and analysis of real-time systems have been established. Among them is Deterministic Network Calculus (DNC), a mathematical framework for worst-case performance modeling and analysis of queuing systems. DNC can derive deterministic bounds on two crucial performance metrics of communication systems:
     (a) the end-to-end delay data flows experience and
     (b) the buffer space required by a server to queue all incoming data.
(Text source: [bib])

This lecture will be an applied Math lecture where theorems and proofs are presented on the whiteboard. An extensive lecture script will be available in the Moodle course. Lecture contents are selected from this script yet they may potentially vary a little. There will be minimalistic slides indicating the selection of content. 

Organization

Literature

  • Jean-Yves Le Boudec and Patrick Thiran. Network Calculus. Springer, 2001. (PDF @author)
  • Cheng-Shang Chang, Performance Guarantees in Communication Networks. Springer, 2000.