Offerta Didattica

 

ENGINEERING AND COMPUTER SCIENCE

COMPUTER SYSTEM DIMENSIONING (yearly)

Classe di corso: LM-32, 18 - Classe delle lauree magistrali in Ingegneria informatica
AA: 2017/2018
Sedi: MESSINA
SSDTAFtipologiafrequenzamoduli
ING-INF/05CaratterizzanteLiberaLiberaNo
CFUCFU LEZCFU LABCFU ESEOREORE LEZORE LABORE ESE
124.501.56036024
Legenda
CFU: n. crediti dell’insegnamento
CFU LEZ: n. cfu di lezione in aula
CFU LAB: n. cfu di laboratorio
CFU ESE: n. cfu di esercitazione
FREQUENZA:Libera/Obbligatoria
MODULI:SI - L'insegnamento prevede la suddivisione in moduli, NO - non sono previsti moduli
ORE: n. ore programmate
ORE LEZ: n. ore programmate di lezione in aula
ORE LAB: n. ore programmate di laboratorio
ORE ESE: n. ore programmate di esercitazione
SSD:sigla del settore scientifico disciplinare dell’insegnamento
TAF:sigla della tipologia di attività formativa
TIPOLOGIA:LEZ - lezioni frontali, ESE - esercitazioni, LAB - laboratorio

Obiettivi Formativi

Acquisire le nozioni su: - Analisi dei sistemi esistenti valutandone il comportamento dal punto di vista delle prestazioni e della affidabilita'. - Determinazione delle componenti di un sistema per ottimizzarne il comportamento. - Definizioni di piani di test per la valutazione di metriche di comportamento di un sistema.

Learning Goals

To learn how to: - Analyse existing systems, evaluating its behaviour in terms of performance and reliability. - Design number and nature of components of a system in order to optimize system behaviour, - Define a test plan for assessment of specific requirements of a system.

Metodi didattici

- Lezioni frontali. - Esercitazioni in laboratorio.

Teaching Methods

- Lectures. - Practical exercises Laboratory.

Prerequisiti

Nozioni di base su: - Teoria delle probabilità e processi stocastici - linguaggi di programmazione

Prerequisites

Basics on: - probability theory and stochastic processes - programming languages

Verifiche dell'apprendimento

- Sviluppo di un semplice progetto. - Discussione sugli argomenti in programma.

Assessment

- Simple project development - Discussion on some specific topics in the area of system design.

Programma del Corso

Performance evaluation: - Basic concepts - Basics on probability theory. Random variables. Probability distribution functions. Operation with random variables. The exponential distributed random variable. - Reliability: definition, failure rate, bath tube curve. Weibull distribution. - Reliability Block Diagram: systems in series, systems in parallel. - Redundancy: component, system, standby, N/K system. - Availability. Availability computation. Mean Time To Failure (MTTF). Mean Time To Repair (MTTR). Availability of systems in series. Availability of parallel system. - Modeling with stochastic Markov chain. - Examples: birth-death processes, availability with different repair policies. - Performability. Reward processes. - Petri nets: formal definition, marking process. Stochastic Petri nets. Generalized stochastic Petri nets. Solution techniques. Stochastic reward nets. Performance and reliability evaluation with Petri nets. - Discrete event simulation. Structure of a discrete event simulator. Random-number generators. Simulation models. Output analysis for a single model: measures of performance and their estimation. Confidence-interval estimation. Output analysis for terminating simulation. Output analysis for steady-state simulation. - Test plan definition. Measurements campaign definition and verification.

Course Syllabus

Performance evaluation: - Basic concepts - Basics on probability theory. Random variables. Probability distribution functions. Operation with random variables. The exponential distributed random variable. - Reliability: definition, failure rate, bath tube curve. Weibull distribution. - Reliability Block Diagram: systems in series, systems in parallel. - Redundancy: component, system, standby, N/K system. - Availability. Availability computation. Mean Time To Failure (MTTF). Mean Time To Repair (MTTR). Availability of systems in series. Availability of parallel system. - Modeling with stochastic Markov chain. - Examples: birth-death processes, availability with different repair policies. - Performability. Reward processes. - Petri nets: formal definition, marking process. Stochastic Petri nets. Generalized stochastic Petri nets. Solution techniques. Stochastic reward nets. Performance and reliability evaluation with Petri nets. - Discrete event simulation. Structure of a discrete event simulator. Random-number generators. Simulation models. Output analysis for a single model: measures of performance and their estimation. Confidence-interval estimation. Output analysis for terminating simulation. Output analysis for steady-state simulation. - Test plan definition. Measurements campaign definition and verification.

Testi di riferimento: "Performance and Reliability Analysis of Computer Systems: An Example-Based Approach Using the SHARPE Software Package"; Robin A. Sahner, Kishor S. Trivedi and Antonio Puliafito; Kluwer Academic Publishers, 1996. "Performability Modelling"; Edited by Boudewijn R. Haverkort, Raymond Marie, Gerardo Rubino, and Kishor Trivedi; Wiley, Chichester, England, 2001. "Discrete-event system simulation"; Jerry Banks; Pearson Prentice Hall, 2005

Elenco delle unità didattiche costituenti l'insegnamento

COMPUTER SYSTEM DIMENSIONING A

Docente: MARCO LUCIO SCARPA
NNomeSSDTipoCFUORETAFFrequenza
1COMPUTER SYSTEM DIMENSIONING AING-INF/05LEZ4,536CaratterizzanteLibera
2COMPUTER SYSTEM DIMENSIONING AING-INF/05ESE1,524CaratterizzanteLibera

Legenda
SEGMENTO: Tutte le unità didattiche sono composte da almeno un segmento
TIPO:LEZ - lezione, ESE - esercitazione, LAB - laboratorio

Orario di Ricevimento - MARCO LUCIO SCARPA

GiornoOra inizioOra fineLuogo
Martedì 09:30 11:30Dipartimento di Ingegneria, Blocco B, piano 7.
Giovedì 09:30 11:30Dipartimento di Ingengeria, Blocco B, piano 7.
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