01TXKSM

A.A. 2020/21

Course Language

Inglese

Course degree

Master of science-level of the Bologna process in Data Science And Engineering - Torino

Course structure

Teaching | Hours |
---|---|

Lezioni | 50 |

Esercitazioni in laboratorio | 30 |

Teachers

Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
---|---|---|---|---|---|---|---|

Meo Michela | Professore Ordinario | ING-INF/03 | 30 | 0 | 10 | 0 | 1 |

Teaching assistant

Context

SSD | CFU | Activities | Area context |
---|---|---|---|

ING-INF/03 | 8 | C - Affini o integrative | Attivitΰ formative affini o integrative |

2020/21

The course provides to student the basic knowledge on performance evaluation via computer simulations, and the skills of using some fundamental methodologies in data processing. Two complementary approaches are discussed. On the one side, the course introduces analytical modeling based on queuing theory and stochastic processes, suitable to study complex systems such as computer networks or transport systems. On the other side, students will be introduced to simulation techniques, which can be applied to study more complex system. Applications of these tools to case studies of practical interest are presented and developed in the activities in the lab.

The course provides to the students the basic knowledge on performance evaluation of dynamic systems via computer simulations, and the skills of using some fundamental methodologies for the assessment, design and understanding of data processing systems.
Two complementary approaches are discussed to study complex discrete systems such as computer networks and data processing systems. On the one side, the course introduces analytical modeling based on queuing theory and stochastic processes. On the other side, students will be introduced to simulation techniques, which can be applied to study the dynamic evolution of a system as a function of time. Applications of these tools to case studies of practical interest are presented and developed in the activities in the lab.

Knowledge of the main elements of a simulator
Ability to evaluate the performance of a dynamic discrete systems through simulation
Ability to understand the fundamental behavior of dynamic discrete systems in terms of its stability, performance characteristics and limits, bottlenecks
Ability to model flows of vehicles, data, people, as well as the interactions among elements of complex dynamic systems
Ability to compare in a quantitative way two dynamic discrete systems

Knowledge of the main elements of a simulator
Ability to evaluate the performance of a dynamic discrete system through simulation
Ability to understand the fundamental behavior of a dynamic discrete system in terms of its stability, performance characteristics and limits, bottlenecks
Ability to model flows of vehicles, data, people, as well as the interactions among elements of complex dynamic systems
Ability to compare in a quantitative way two dynamic discrete systems

Basic knowledge of probability theory. Basic programming skills (python).

Basic knowledge of probability theory. Basic programming skills (python).

Basic concepts of performance evaluation
Discrete-event and process simulation
Fitting empirical distributions
Simulating traffic sources
Mobility models
Analysis of the output
Identification of transients
Analysis of transient behaviors
Basic concepts of queuing systems
Queuing systems in isolation
Load and system stability
Little's law
Queuing networks
Case studies

Basic concepts of performance evaluation
Discrete-event and process simulation
Fitting empirical distributions
Simulating traffic sources
Mobility models
Analysis of the output
Identification of transients
Analysis of transient behaviors
Basic concepts of queuing systems
Queuing systems in isolation
Load and system stability
Little's law
Queuing networks
Case studies

50 h lectures (L)
30 h lab (EL)

50 h lectures (L): besides traditional theoretical classes, several problems will be proposed, discussed and solved
30 h lab (EL)

The teaching material will be provided by the teachers on the web portal.

The teaching material will be provided by the teachers on the web portal.

The exam will consist of three parts.
1) A written exam, of the duration of 1.5 h, will be done with the support of the exam platform and proctoring system.
2) A report on the lab activities.
3) An oral exam to discuss both the lab activities and the written exam.

The exam will consist of three parts.
1) A written exam, of the duration of 1.5 h, will be done with the support of the exam platform and proctoring system.
2) A report on the lab activities.
3) An oral exam to discuss both the lab activities and the written exam.

The exam will consist of three parts.
1) A written exam, of the duration of 1.5 h, will be done with the support of the exam platform and proctoring system or in the classroom.
2) A report on the lab activities.
3) An oral exam to discuss both the lab activities and the written exam.

The exam will consist of three parts.
1) A written exam, of the duration of 1.5 h, will be done with the support of the exam platform and proctoring system or in the classroom.
2) A report on the lab activities.
3) An oral exam to discuss both the lab activities and the written exam.

© Politecnico di Torino

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY