Modeling Seminar for Engineers

A tantárgy neve magyarul / Name of the subject in Hungarian: Mérnöki modellalkotás - az elmélettől a gyakorlatig

Last updated: 2018. június 19.

Budapest University of Technology and Economics
Faculty of Electrical Engineering and Informatics
Course ID Semester Assessment Credit Tantárgyfélév
VITMMA03 2 2/1/0/v 4  
3. Course coordinator and department Dr. Babarczi Péter,
Web page of the course http://www.tmit.bme.hu/vitmma03
4. Instructors
Name: Title: Department:
 Dr. József Bíró, DSc
 Professor TMIT
 Dr. Péter Babarczi, PhD
 Assist. Prof
 TMIT
 Attila Kőrösi  Dept. Engineer
 TMIT
5. Required knowledge Algorithms, theory of computing
6. Pre-requisites
Kötelező:
NEM ( TárgyEredmény( "BMEVITMM215" , "jegy" , _ ) >= 2
VAGY
TárgyEredmény("BMEVITMM215", "FELVETEL", AktualisFelev()) > 0)

A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

7. Objectives, learning outcomes and obtained knowledge

The students will learn the most important engineering challenges and design objectives of communication networks, ranging from small local networks through the core to the Internet. The students will see the most widespread mathematical techniques of modeling the engineering problems in communication networks, and during the course they will learn their application. Through the models the students can apply in practical use cases (e.g., Internet routing, topology, traffic and bandwidth planning) the previously learnt mathematical and algorithmic knowledge form their computer science studies.

8. Synopsis

·         IP forwarding and compressed data structures

o   IP addressing. IP forwarding, scalability issues

o   Prefix tree compression, information-theoretic bound, lookup on compressed data structures

·         Efficient bandwidth utilization with coding

o   Network bandwidth planning, multicast forwarding

o   Demonstrating the efficiency of mathematical models through a network coding use case

·         Virtual network design

o   Practical implementations of virtual networks over the physical infrastructure (cloud computing, SDN, etc.)

o   Virtual network embedding into the physical topology

·         Internet traffic modeling

o   Introduction into traffic modeling

o  Demonstrating the existence of equivalent formulas on the Internet to the simple Erlang-formula in the telecommunication networks

·         Network dimensioning with network calculus

o   Classical queuing system: incoming (aggregated traffic) packets, buffer, server

o   Simplifying the involved queuing theory models with the application of network calculus

·         Internet traffic engineering

o   Fluid model of the TCP closed loop control, continuous feedback systems, controllers

o  TCP (and newer version) congestion control, network stability analysis, network stability guarantees

9. Method of instruction

Weekly lectures, and practice every second week. The theoretical models shown on the lectures are applied on relevant use cases in the practical lecture. Preparing the home works affect the final grade.

10. Assessment

a)      Lecture period: preparing home works

b)      Exam period: written and oral exam

12. Consultations

During lectures, or upon request.

13. References, textbooks and resources

For every topic the recommended papers from the literature will be given.

R. Koetter and M. Médard, "An algebraic approach to network coding," IEEE/ACM Trans. on Networking, vol. 11, no. 5, pp. 782-795, 2003

Bonald, Thomas, and James W. Roberts. "Internet and the Erlang formula." ACM SIGCOMM Computer Communication Review vol. 42 no. 1, pp. 23-30, 2012

Le Boudec, J. Y., Thiran, P. Network calculus: a theory of deterministic queuing systems for the internet (Vol. 2050). Springer. 2001

 

14. Required learning hours and assignment
Lectures42
Preparation for lectures
14
Preparation for mid-term exam
-
Home works36
Literature-
Preparation for exams
28
Total120
15. Syllabus prepared by
Name: Title: Department:
 Dr. Gábor Rétvári, PhD
 Research Fellow
 TMIT
 Dr. András Gulyás, PhD
 Assoc. Prof TMIT
 Dr. József Bíró, DSc Professor TMIT
 Dr. Péter Babarczi, PhD
 Assist. Prof  TMIT