Szolgáltatásbiztonság sztochasztikusmodell-alapú kiértékelése

1.      Foundational elements - it will discuss the basic and foundational concepts on dependability, the role played by stochastic modeling approaches as a system validation technique, and it will recall some basics on probability theory. Topics covered:

a.       Basics on dependability, on performance and reliability analysis of systems and on systems validation.

b.      Definitions of performances and reliability indicators.

c.       Rules for building and validating models.

d.      Fundamentals of probability theory.

2.      Combinatorial methods - it will focus on several combinatorial approaches for quantitative and qualitative dependability assessment. Topics covered:

a.       Boolean methods.

b.      Fault Trees, Reliability Block Diagrams, Reliability Graphs.

c.       Examples and guided exercises.

3.      Markovian Processes - it focuses on the usage of the Markovian processes for describing a system state and its evolution, covering both transient and steady-state analysis of Discrete and Continuous Time Markov Chains. Topics covered:

a.       Introduction to Random Processes and to Markovian Processes.

b.      Discrete Time Markov Chains - Transient and Steady-state analysis.

c.       Continuous Time Markov Chains - Transient and Steady-state analysis.

d.      Examples and guided exercises.

4.      Petri Nets (PN) and extensions - it will focus on Petri Nets models, starting from the basic PN and considering several PN extensions. Topics covered:

a.       Intro to PN.

b.      Priority and Timed PN.

c.       Stochastic Petri Nets.

d.      Generalized Stochastic Petri Nets.

e.       Examples and guided exercises.

5.      Stochastic Activity Networks (SAN) - it will focus on Stochastic Activity Networks as a general and powerful stochastic modeling formalisms widely adopted for performability analysis, and on its supporting tool Möbius for the practical modeling exercises during the lectures. Topics covered:

a.       Introduction, Definition, Completion rules, Stabilizing and Well-Specified SAN. Underlying stochastic process.

b.      Automatic supporting tools: Möbius.

c.       Guided practical modelling experiences using SAN and Möbius tool.