Servizi per la didattica
PORTALE DELLA DIDATTICA

Computer aided simulations and performance evaluation

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
Espandi
Context
SSD CFU Activities Area context
ING-INF/03 8 C - Affini o integrative Attivitΰ formative affini o integrative
Date d'appello
Orario delle lezioni
Statistiche superamento esami
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.
Modalitΰ di esame: Prova orale obbligatoria; Prova scritta tramite PC con l'utilizzo della piattaforma di ateneo; Elaborato progettuale in gruppo;
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.
Exam: Compulsory oral exam; Computer-based written test using the PoliTo platform; Group project;
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.
Modalitΰ di esame: Test informatizzato in laboratorio; Prova orale obbligatoria; Prova scritta tramite PC con l'utilizzo della piattaforma di ateneo; Elaborato progettuale in gruppo;
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.
Exam: Computer lab-based test; Compulsory oral exam; Computer-based written test using the PoliTo platform; Group project;
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.
Esporta Word
© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti