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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

News

  • The lecture is over.

Overview

Information
Lecturers:
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))
Area:
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)

Module:
MINF-KT-NOR.S11
SWS:
4
ECTS/LP:
6
Time:
Thursdays, 12 a.m. – 4 p.m. weekly

First Meeting:
21 April 2011
Room:
FR 1067
Audience:
bachelor students after their basic studies (from the fifth semester on), master students, and Diplom students
Prerequisites:
  • 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
Exam:
written. Further information tba

Further information:
see ISIS

Organization

Registration

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.

Homework

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

Exam

Written exam, further detailes tba

Ressources

Literature

  • 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)

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions

Registration at Prüfungsamt

Exam and module
registration at INET
take place via the
Prüfungsamt (exam
office).

Network Optimization by Randomization
0432 L 816
Integrierte LV (VL mit UE)

Lecturer: Florin Ciucu, Stefan Schmid, Anja Feldmann

Period:
21.04.2011 to 21.07.2011

Th 12:00 - 16:00 o'clock

Location: FR 1067, Fino (TEL 16)

Website
ISIS

Complete domains

...of e-mail addresses
@inet =
@inet.tu-berlin.de
@tub = @tu-berlin.de