Basics on performance and reliability analysis of systems and on systems validation. Fundamentals of probability theory and combinatorial methods. Discrete time and continuous time Markov processes. Stochastic Petri Nets. Modeling formalisms: PN and extensions. Automatic tools: Möbius and Deem. Fundamentals of measurement theory and its application. System testing: functional, fault injection, robustness. Planning of experimental campaigns. Dependability benchmarking. Supporting tools for experimental evaluation: NekoStat.
“L’Analisi Quantitativa dei Sistemi Critici”, a cura di Andrea Bondavalli, Società Editrice Esculapio, ISBN 978-88-7488-431-5, Prima edizione, 286 pagine, Marzo, 2011.
Learning Objectives
The course provides students with the notions required to understand aspects of quantitative analysis and of quality of the service offered by computing systems, with emphasis on the analysis of performances and reliability.
Prerequisites
None
Teaching Methods
CFU: 9
Total hours of the course: 270
Hours reserved to private study and other individual formative activities: 198
Prof. Andrea Bondavalli, by appointment.
Contact professor by phone number or e-mail (bondavalli@unifi.it).
DiMaI, Universita' di Firenze, Viale Morgagni, 65 - 50134 Firenze
Tel. 055 2751481
Dott. Andrea Ceccarelli, by appointment.
Contact professor by phone number or e-mail (andrea.ceccarelli@unifi.it).
DiMaI, Universita' di Firenze, Viale Morgagni, 65 - 50134 Firenze
Tel. 055 2751487
Dott. Silvano Chiaradonna, by appointment.
Contact professor by phone number or e-mail (silvano.chiaradonna@isti.cnr.it).
Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo" (ISTI-CNR) Area della Ricerca CNR di Pisa, Via G. Moruzzi, 1
56124 Pisa, Italy
Tel. 050 3153005 (3152909)
Type of Assessment
The Assessment consists of two parts:
- Development of a specific investigation on a topic of the course or an evaluation project;
- Oral interview.
Conditional to the oral interview is the acceptance of the report on the project.
Course program
Basics on performance and reliability analysis of systems and on systems validation. Definitions of performances and reliability indicators. Rules for building and validating models. Fundamentals of probability theory. Combinatorial methods. Discrete time Markov processes. Continuous time Markov processes. Queue theory: the MM1 queue and its variants. Stochastic Petri Nets. Modeling formalisms: PN and extensions (e.g., SAN, DSPN). Automatic supporting tools: Möbius and Deem. Fundamentals of measurement theory and its application. System testing: functional, fault injection, robustness. Planning of experimental campaigns. Dependability benchmarking. Supporting tools for testing: NekoStat.