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Internet Network ArchitecturesNetwork Optimization by Randomization (IV)

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Network Optimization by Randomization (Integrated course, SoSe 2011)

All modern computer and wireless networks include a random component. Concrete applications of randomness abound in as diverse fields as communication protocols, network security, or distributed computing. By taking this module the students will be capable to understand:

  1. a set of general principles underlying the essence of randomness for network protocol design: foiling the adversary, random sampling, load balancing, or symmetry breaking
  2. the benefits of randomness, e.g., in terms of simplicity, efficiency, or fast execution times, for network optimization

Moreover, the students will be able to make judicios use of randomness when developing new network protocols.

The lectures mix basic elements from probability directly applicable to practical problems in network protocol design and analysis. A tentative outline of the main topics to be covered in the course are

  • Multiple Access Protocols
  • Scheduling (e.g., backpressure, opportunistic, approximate)
  • Flow & Congestion Control, Routing
  • Resource Allocation (e.g., energy, bandwidth, CPU)
  • Peer-to-Peer & Social Networks
  • Online Algorithms
  • Network Security
  • Network Coding
  • Network Reliability


  • The lecture is over.


Anja Feldmann, Florin Ciucu
in addition: Stefan Schmid
additional contact person:
Oliver Hohlfeld
Event type:
Integrated course (lecture with tutorial)
(Integrierte Veranstaltung (Vorlesung mit Übung))
Diplom Informatik: Operating and Communication Systems / Betriebs- und Kommunikationssysteme (BKS)
Master of Computer Science: Communication-Based Systems (Master Informatik: Kommunikations­basierte Systeme)
Master of Computer Engineering: Technical Applications (Master Technische Informatik: Technische Anwendungen)

Thursdays, 12 a.m. – 4 p.m. weekly

First Meeting:
21 April 2011
FR 1067
bachelor students after their basic studies (from the fifth semester on), master students, and Diplom students
  • BINF-GL-MPGI 1: Algorithmische und funktionale Lösung diskreter Probleme
  • BINF-GL-MPGI 2: Algorithment und Datenstrukturen im imperativen Stil
  • BINF-GL-StochInf: Stochastik für Informatiker
or equivalent

  • Englisch
written. Further information tba

Further information:
see ISIS



If you are interested in attending, please make sure you are subscribed to this course in ISIS to receive information and announcements.

A module registration is also obligatory for Master studetns. Further information will be given in the lecture or via ISIS.


There will be a tutorial within the course. You need 50% of the possible points to pass the tutorials.


Written exam, further detailes tba



  • M.J. Neely. Stochastic Network Optimization with Application to Communication and Queueing Systems. Morgan & Claypool, 2010 (english)
  • Michael Mitzenmacher and Eli Upfal. Probability and Computing. Cambridge University Press, 2005 (english)
  • David Peleg. Distributed Computing: A Locality-Sensitive Approach. SIAM, Philadelphia, PA, USA, 2000. (english)
  • Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, and Walter Unger. Dissemination of Information in Communication Networks. Springer. 2005 (english)
  • Thomas Cormen, Charles Leiserson, and Ronald Rivest. Introduction to Algorithms. The MIT Press, 1998 (english)
  • J. Kleinberg. Navigation in a Small World. Nature, Volume 406(2000), 845 (pdf)


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