Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Modeling Seminar for Engineers

    A tantárgy neve magyarul / Name of the subject in Hungarian: Mérnöki modellalkotás szeminárium

    Last updated: 2024. február 26.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

     Villamosmérnöki Tudományok Doktori Iskola és Informatikai Tudományok Doktori Iskola

    választható tárgy
    Course ID Semester Assessment Credit Tantárgyfélév
    VITMD099   4/0/0/v 5  
    3. Course coordinator and department Dr. Babarczi Péter,
    4. Instructors

    Név:

    Beosztás:

    Tanszék, Int.:

    Dr. Péter Babarczi PhD

    Associate Professor

    Department of Telecommunications and Media Informatics 

    Dr. András Gulyás PhD

    Research Fellow

    Department of Telecommunications and Media Informatics 

    Dr. József Bíró DSc

    		Professor

    Department of Telecommunications and Media Informatics 

    Dr. Gábor Rétvári PhD

    Research Fellow

    Department of Telecommunications and Media Informatics 

    5. Required knowledge Introduction to the Theory of Computing, Theory of Algorithms
    6. Pre-requisites
    Ajánlott:
    No pre-requisites. 
    7. Objectives, learning outcomes and obtained knowledge In this course we introduce the most important engineering challenges of infocommunication networks and their design questions ranging from small networks to the Internet core. The students can learn the mathematical models of different engineering problems, which they can try themselves on small examples during the course. Through coding examples, the theoretical models can be realized in practice. Using different coding platforms, they can compare their solutions with each other, improve and deepen their algorithmic knowledge learned during their previous studies by applying them to the examples of Internet traffic-, topology-, routing- and bandwidth-design. 
    8. Synopsis

    • Network science 

    • Introducing mathematical models for real-world networks, important structural characteristics, measures and the effect of these parameters on performance and resilience 

    • Classical models and networks (e.g.: small-world, Erdős-Rényi, Barabási-Albert, hyperbolic), their properties and applicability 

    • Statistical multiplexing and bandwidth estimation 

    • Classical queuing theory systems: incoming packets (from aggregated traffic flows), buffering, modelling servers for modern VoIP codecs 

    • Using network calculus to simplify the previous involved queuing theory models, modelling and analyse the aggregate speed of on-off flows  

    • Efficient bandwidth utilization with network coding 

    • Bandwidth allocation for networks with algebraic operations, efficient multicast bandwidth utilization, introduction to robust routing and other classical examples 

    • Demonstrating the description power of different mathematical models for network coding, message coding and decoding over finite fields 

    • Virtual network design 

    • Practical implementations of virtual networks over physical infrastructures (cloud computing, resource allocation, virtual SDN topology embedding, etc.) 

    • Efficient resource allocation for virtual networks, intelligent virtual node and link embedding to physical resources, robust path design solutions 

    • IP forwarding and compressed data structures 

    • Introduction to IP addressing, IP forwarding, scalability issues and the possible engineering solutions for them 

    • Prefix-tree compression, information-theoretic bounds, efficient lookup on compressed data structures 

    9. Method of instruction Lectures. 
    10. Assessment

    1. Lecture Period: homework assignments belong to each topic, which should be solved at least on a sufficient level for the signature. 

    1. Exam period: Oral exam 

    11. Recaps One homework assignment can be submitted late on the week of repeats. 
    12. Consultations During lectures, or upon request. 
    13. References, textbooks and resources We give the necessary literature for each topic and make further learning material available on the lecture’s website. 
    14. Required learning hours and assignment
    Lectures56
    Preparation for lectures
    		14
    Preparation for mid-term exam
    		-
    Home works50
    Literature10
    Preparation for exams
    		20
    Total150

    15. Syllabus prepared by

    Name: 

    Title: 

    Department: 

    Dr. András Gulyás PhD 

    Research Fellow 

    Department of Telecommunications and Media Informatics 

    Dr. Péter Babarczi PhD 

    Associate Professor 

    Department of Telecommunications and Media Informatics