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

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    Performance Evaluation of Infocommunication Systems

    A tantárgy angol neve: Performance Evaluation of Infocommunication Systems

    Adatlap utolsó módosítása: 2016. november 4.

    Budapesti Műszaki és Gazdaságtudományi Egyetem
    Villamosmérnöki és Informatikai Kar

    Electrical Engineering, Free Elective Course

    Software Engineering, Free Elective Course

    Tantárgykód Szemeszter Követelmények Kredit Tantárgyfélév
    VITMAV24   3/1/0/v 4  
    3. A tantárgyfelelős személy és tanszék Dr. Molnár Sándor, Távközlési és Médiainformatikai Tanszék
    4. A tantárgy előadója Dr. Sándor Molnár
    5. A tantárgy az alábbi témakörök ismeretére épít Basic knowledge of probability theory and infocommunication systems
    6. Előtanulmányi rend
    Ajánlott:
    The course cannot be taken for students who already took VITMM325 Performance Evaluation of Infocommunication Systems.
    7. A tantárgy célkitűzése

    The course is concerned with introducing the students to the theoretical tools to carry out performance evaluations of infocommunication systems. It also gives practical case studies how to apply these tools.

    8. A tantárgy részletes tematikája

    Introduction to Internet Traffic Theory

    Week 1: Review of probability theory and stochastic processes

    Fundamental theorems of probability theory which are extremely important in traffic modeling and performance evaluation of communication systems. The definition and interpretation of stochastic processes. Applications of stochastic processes in modeling.

    Week 2: Traffic characterization by point processes

    The definition of point processes. The application of point processes for internet traffic characterization. The stationarity of point processes. The description of point processes. The process of intervals between events. The counting process. The selection of origin in traffic modeling by point processes.

    Week 3: Burst and correlation measures

    Interpretation of burst and correlation and their impacts on Internet traffic. First and second order characterization of burst and correlation measures. Squared coefficient of variation. Peak to mean ratio. Probability distribution function. Moments. Correlation of interarrival times. Correlation of counts. Index of dispersion for intervals (IDI). Index of dispersion for counts (IDC). Variance time plot. Relationships between measures.

    Week 4: Case study for traffic analysis: from measurements to modeling

    Case study for selected traffic sources: renewal processes, correlated processes, aggregated traffic, voice traffic, video traffic. Burst and correlation analysis demonstrated for the case study traffic sources with lots of figures and interpretation of results. Study guides for traffic analysis by interpreting results of actual measured Internet traffic.

    Week 5: Traffic models based on Poisson processes

    Derivation, definitions and basic properties of Poisson processes. Traffic models based on Poisson processes: inhomogeneous Poisson process, batch Poisson process, Markov Modulated Poisson Process (MMPP) and their use for traffic modeling.

    Week 6: Traffic characterization by renewal processes

    Definition and basic properties of renewal processes. Characterization of traffic aggregation and traffic splitting in Internet routers. Traffic models based on renewal processes. Application guide for renewal-based traffic models.

    Week 7: Advanced traffic models (voice, video, web, etc.)

    How to choose traffic models for measured traffic? The goal and use of advanced traffic models. Web traffic models. P2P traffic models, gaming traffic models, VoIP traffic models, advanced video traffic models. How to set the parameters of traffic models.

    Week 8: Introduction to fractal traffic theory

    Fractal properties of Internet traffic. Self-similarity and long-range dependence. Heavy-tailed distributions in the Internet. Fractal traffic analysis. Fractal traffic models. Examples of using fractal traffic models.

    Internet Traffic Management

    Week 9: Overprovisioning and managed bandwidth

    Traffic management philosophies. The overprovisioning approach. The managed bandwidth method. Advantages and disadvantages of traffic management approaches. Traffic characteristics of stream traffic and elastic traffic. Which approach to choose?

    Week 10: Traffic control, connection admission control and traffic dimensioning

    Traffic categories vs. traffic control approaches. Open loop control. Peak rate allocation. Rate envelope multiplexing. Rate sharing. Statistical multiplexing. Packet scale and burst scale congestion. Designing principles of traffic control methods. Case study: Gaussian approximation.

    Week 11: Future internet design principles and case studies

    Trends in future internet design and dimensioning. Lessons from the past for the future. Case studies chosen from current research papers.

    Performance evaluation of TCP

    Week 12: Evolution of TCP:  loss- and delay-based TCP and high-speed TCP versions

    Principle of TCP (Transmission Control Protocol) congestion control. Loss-based TCP variants (Reno, BIC, CUBIC, etc.). Delay-based TCP variants (Vegas, FAST, etc.). Hybrid TCP versions (Compound TCP, Westwood , etc.), TCP versions for high-speed communications (H-TCP, etc.).

    Week 13: Performance models of TCP

    Models for TCP. A simple TCP model and its detailed analysis. Throughput calculation based on TCP models. Advanced TCP models. Application of TCP models in network design and dimensioning.

    Week 14: Case study of TCP performance evaluation

    Case study: networking examples for performance evaluations of TCP-based communication. QoS characteristics calculations. Throughput and latency calculations. Numerical examples of real internet communications solved by TCP models.

    9. A tantárgy oktatásának módja (előadás, gyakorlat, laboratórium) Lecture and practice
    10. Követelmények

    1. In the semester period there is an in-class test (ZH) to get the signature.

    2. In the exam period: written exam.

    11. Pótlási lehetőségek Failed in-class test (ZH) can be repeated in the semester period. Failed in-class test (ZH) and repeated failed in-class test (ZH) can be repeated in the exam period with paid fee.
    12. Konzultációs lehetőségek On demand
    13. Jegyzet, tankönyv, felhasználható irodalom
    1. H. Tijms, A First Course in Stochastic Models, Wiley 2003
    2. M. Welzl, Network Congestion Control: Managing Internet Traffic, Wiley 2005
    3. Selected conference and journal publications from recent literature
    14. A tantárgy elvégzéséhez átlagosan szükséges tanulmányi munka
    Kontakt óra56
    Félévközi készülés órákra20
    Felkészülés zárthelyire4
    Házi feladat elkészítése0
    Kijelölt írásos tananyag elsajátítása0
    Vizsgafelkészülés40
    Összesen120
    15. A tantárgy tematikáját kidolgozta Sándor Molnár, PhD, Department of Telecommunications and Media Informatics