Moduł oferowany także w ramach programów studiów:
Informacje ogólne:
Nazwa:
Modelling and simulation of networks and services
Tok studiów:
2019/2020
Kod:
IETE-2-233-s
Wydział:
Informatyki, Elektroniki i Telekomunikacji
Poziom studiów:
Studia II stopnia
Specjalność:
-
Kierunek:
Electronics and Telecommunications
Semestr:
2
Profil:
Ogólnoakademicki (A)
Język wykładowy:
Polski
Forma studiów:
Stacjonarne
Strona www:
 
Prowadzący moduł:
dr hab. inż. Szott Szymon (szott@kt.agh.edu.pl)
Treści programowe zapewniające uzyskanie efektów uczenia się dla modułu zajęć

The aim of the module is to learn the methodology of research on the efficiency of telecommunications systems using analytical and simulation models.

Opis efektów uczenia się dla modułu zajęć
Kod MEU Student, który zaliczył moduł zajęć zna i rozumie/potrafi/jest gotów do Powiązania z KEU Sposób weryfikacji i oceny efektów uczenia się osiągniętych przez studenta w ramach poszczególnych form zajęć i dla całego modułu zajęć
Wiedza: zna i rozumie
M_W001 Has in-depth knowledge of analytical modeling of network systems and services. Has in-depth knowledge of probability (random number generators) and statistics (central tendency, system variability, confidence intervals) needed to conduct simulation analysis of ICT networks and to develop simulation results. ETE2A_W01 Kolokwium,
Egzamin
M_W002 Has structured knowledge in the field of analysis of wired and wireless ICT networks using analytical tools and using a discrete event simulator. ETE2A_W02 Kolokwium,
Egzamin
M_W003 Has deepened and structured knowledge in the field of modeling and simulation of ICT networks and is able to compare the results obtained with experimental results. ETE2A_W03 Kolokwium,
Egzamin
Umiejętności: potrafi
M_U001 He can use technical documentation for simulation software. ETE2A_U01 Projekt
M_U002 Is able to develop detailed documentation of the results of the simulation experiment, including justification of the adopted simplifications, configuration of simulation scenarios, description of statistical analysis and conclusions. ETE2A_U03 Projekt
M_U003 Is able to carry out a simulation analysis of a teleinformation network taking into account the time of simulator warmup. ETE2A_U04 Projekt
Kompetencje społeczne: jest gotów do
M_K001 He is able to creatively solve problems related to the configuration and running of simulation scenarios and the processing of result data. ETE2A_K01 Projekt
Liczba godzin zajęć w ramach poszczególnych form zajęć:
SUMA (godz.)
Wykład
Ćwicz. aud
Ćwicz. lab
Ćw. proj.
Konw.
Zaj. sem.
Zaj. prakt
Zaj. terenowe
Zaj. warsztatowe
Prace kontr. przejść.
Lektorat
60 0 0 0 30 30 0 0 0 0 0 0
Matryca kierunkowych efektów uczenia się w odniesieniu do form zajęć i sposobu zaliczenia, które pozwalają na ich uzyskanie
Kod MEU Student, który zaliczył moduł zajęć zna i rozumie/potrafi/jest gotów do Forma zajęć dydaktycznych
Wykład
Ćwicz. aud
Ćwicz. lab
Ćw. proj.
Konw.
Zaj. sem.
Zaj. prakt
Zaj. terenowe
Zaj. warsztatowe
Prace kontr. przejść.
Lektorat
Wiedza
M_W001 Has in-depth knowledge of analytical modeling of network systems and services. Has in-depth knowledge of probability (random number generators) and statistics (central tendency, system variability, confidence intervals) needed to conduct simulation analysis of ICT networks and to develop simulation results. - - - + + - - - - - -
M_W002 Has structured knowledge in the field of analysis of wired and wireless ICT networks using analytical tools and using a discrete event simulator. - - - + + - - - - - -
M_W003 Has deepened and structured knowledge in the field of modeling and simulation of ICT networks and is able to compare the results obtained with experimental results. - - - + + - - - - - -
Umiejętności
M_U001 He can use technical documentation for simulation software. - - - + - - - - - - -
M_U002 Is able to develop detailed documentation of the results of the simulation experiment, including justification of the adopted simplifications, configuration of simulation scenarios, description of statistical analysis and conclusions. - - - + - - - - - - -
M_U003 Is able to carry out a simulation analysis of a teleinformation network taking into account the time of simulator warmup. - - - + - - - - - - -
Kompetencje społeczne
M_K001 He is able to creatively solve problems related to the configuration and running of simulation scenarios and the processing of result data. - - - + - - - - - - -
Nakład pracy studenta (bilans punktów ECTS)
Forma aktywności studenta Obciążenie studenta
Sumaryczne obciążenie pracą studenta 118 godz
Punkty ECTS za moduł 4 ECTS
Udział w zajęciach dydaktycznych/praktyka 60 godz
przygotowanie projektu, prezentacji, pracy pisemnej, sprawozdania 28 godz
Samodzielne studiowanie tematyki zajęć 30 godz
Szczegółowe treści kształcenia w ramach poszczególnych form zajęć (szczegółowy program wykładów i pozostałych zajęć)
Ćwiczenia projektowe (30h):
  1. Part 1. Simulation basics

    In the first part the student obtains knowledge about the following areas:
    1. Goal of modeling and simulation. Definitions. When simulation is the appropriate tool. Advantages/disadvantages of simulation. Areas of application. System terminology. Models of a system. Performance metrics. Characterizing a simulation model. Types of models and simulators. Simulation examples. Simulation study. Simulation languages and packages.
    2. Discrete-event model. Future event list. Event scheduling.
    3. Basics of random number generation. Generating random numbers from uniform and other distributions. Tests of uniformity tests and independence.
    4. Steady-state and transient simulations. Central tendency. System variability. Confidence intervals. Data collection and analysis techniques.
    5. Main simulation steps. Connections and applications. Random variables. Queuing models. Result processing and visualization. Confidence intervals – result validation.

  2. Part 2. Simulation analyses

    In the second part, the student performs a simulation analysis of a given network considering the techniques learned in part one.

Konwersatorium (30h):
Modelling of telecommunication networks and servies

1. Modelling telecommunication networks
Modelling methods and purposes. Pareto rule in modelling. QoE and QoS metrics. Qos controls.

2. Exponential teletraffic models
Definition of session. Teletraffic and Qos controls on different time scales. Count, instantaneous, and fluid teletraffic models. Traffic intensity. Poisson counting model and instantaneous exponential model. Properties of the Poisson and exponential teletraffic models (meymorylessness, PASTA, inspection time paradox, binomial approximation). Multiphase exponential models. Renewal process.

3. Markov processes in teletraffic modelling
Poisson process as a birth process. Markov process as a random walk over graph. Evolution of Markov process (transient and stationary states). Decomposition of Markov process to sojourn times and embedded Markov chain. Semi-Markov processeses.

4. M/M/1 queue as a model of packet transmission
Kendall notation. Evolution of a M/M/1 queue (transient and stationary states). Solutions of M/M/1 stationary state equations. M/M/1 queue with state dependent parameters.

5. Little’s theorem. QoS metrics (throughput, delay, occupation) for M/M/1 queue. Optimum operating point of M/M/1 queue. M/M/1/N queue. M/G/1 queue (Pollaczek-Kchinchin theorem) and M/G/1 queue. Selfsimilar traffic and SS/M/1 queue.

6. Markovian open networks
Packet processing in networks (buffering, routing, multiplexing). Burke’s theorem. State probability distribution for open Markovian networks. Optimization of network metrics.

7. Markovian closed netowrks
Open M/M/1/N queue as a clsed queue. MVA algorithm. State probability distribution for closed Markovian networks. Optimization of window flow control. BCMP models.

Pozostałe informacje
Metody i techniki kształcenia:
  • Ćwiczenia projektowe: Students carry out the project on their own without major intervention. This is to create a sense of responsibility for group work and responsibility for making decisions.
  • Konwersatorium: During the seminar classes, students solve the problems they have previously asked. The lecturer systematically applies the explanations and moderates the discussion with the group over the given problem.
Warunki i sposób zaliczenia poszczególnych form zajęć, w tym zasady zaliczeń poprawkowych, a także warunki dopuszczenia do egzaminu:

1. To pass the course it is necessary to get at least a satisfactory grade (3.0) from the project exercises, a positive grade from the seminar and passing the exam.
2. The evaluation of the tutorials is issued on the basis of tests.
3. The evaluation of project exercises is issued on the basis of a written report.
4. The student has the right to pass an oral amendment.

Zasady udziału w zajęciach:
  • Ćwiczenia projektowe:
    – Obecność obowiązkowa: Tak
    – Zasady udziału w zajęciach: Students carry out practical work aimed at obtaining competences assumed by the syllabus. The project implementation method and the final result are subject to evaluation.
  • Konwersatorium:
    – Obecność obowiązkowa: Tak
    – Zasady udziału w zajęciach: Students attending conversational classes are obliged to prepare themselves in the scope indicated by the teacher each time. The assessment of the student's work is based on oral and written statements, which, according to the AGH study regulations, translates into the final grade form this form of classes.
Sposób obliczania oceny końcowej:

The final grade is calculated as a weighted average of grades from project exercises (30%), the seminar (30%) and the exam (40%) (from all attempts).

In the case of calculating any grade based on the points obtained, the thresholds according to §13, point 1 of the Regulations of Studies. In the case of calculating any assessment based on the weighted average of other assessments, the same thresholds as defined in §27, point 4 of the Regulations of Studies.

Sposób i tryb wyrównywania zaległości powstałych wskutek nieobecności studenta na zajęciach:

The individual mode of compensating any shortages in knowledge resulting from the absence of a student during classes is determined each time by the teacher.

Wymagania wstępne i dodatkowe, z uwzględnieniem sekwencyjności modułów :

Prerequisites:
1. Networking basics
2. Stochastic modelling
3. Probability and statistics

Zalecana literatura i pomoce naukowe:

Project classes:
1. G. Wainer, „Discrete-Event Modeling and Simulation”
2. K. Wehrle, M. Günes, J. Gross, „Modeling and Tools for Network Simulation”
3. M. Guizani, A. Rayes, B. Khan, A. Al-Fuqaha, „Network Modeling and Simulation: A Practical Perspective”
4. J. Banks, J. Carson, B. Nelson, D. Nicol, „Discrete-Event System Simulation”
Conversation seminar:
1. L. Kleinrock, “Queueing Systems – Vol. I: Theory”, John Wiley & Sons 1975
2. D. Bertsekas, R. Gallager, “Data Networks”, Prentice Hall 1993
3. L. Lipsky, “Queueing Theory – A Linear Algebraic Approach”, University of Connecticut, 2008
4. M. Zukerman, “Introduction to Queueing Theory and Stochastic Teletraffic Models”, EE Department, City University of Hong Kong

Publikacje naukowe osób prowadzących zajęcia związane z tematyką modułu:

1. S. Szott, M. Natkaniec i inni, “Evaluating New Concepts in Wireless Communications: From Theory to Practice”, European Wireless 2016; 22nd European Wireless Conference, 2016.
2. Z. Papir, “Ruch telekomunikacyjny i przeciążenia sieci pakietowych”, WKiŁ 2001
3. K. Rusek, L. Janowski, Z. Papir, “Transient and stationary characteristics of a packet buffer modelled as an MAP/SM/1/BSystem”, International Journal of Applied Mathematics and Computer Science, vol. 24 no. 2, 2014, s. 429–442.
4. J. Rachwalski, Z. Papir, “Burst ratio in concatenated Markov-based channels”, Journal of Telecommunications and Information Technology, nr 1, 2014, s. 3–9.

Informacje dodatkowe:

Brak