Content, progress and pedagogy of the module

Learning objectives

Knowledge

The students must have insight in:

• traffic modelling including heavy tailed behavior
• renewal processes, self-similar traffic and long-range dependence
• advanced queuing models, including matrix analytical and matrix exponential models
• different types of faults that can occur during the operational phase of a communication system
• dependability concepts; availability & reliability for parallel and serial systems
• methods for fault-detection and fault-recovery, incl Markov chain models for systems with faults
• Hidden Markov models for fault detection

Skills

Students must be able to

• apply simple and advanced traffic and queuing models, in performance analysis of real-life traffic systems
• create realistic traffic models, based on knowledge on the behavior of relevant components including users and applications and/or on knowledge of existing traffic
• list the different considered faults, how they propagate through the system and assess their severity and occurrence likelihood
• quantitatively assess the impact of faults on system availability and system reliability
• apply methods for fault-detection and recovery to complex networked systems, including cyber-physical systems
• Develop fault tolerant strategies for ensuring the continuation of the system in the presence of faults

Competences

The students must be able to

• select the appropriate queuing and traffic models to be used in the modeling of a specific system, analyse them and apply
• Select fault-tolerant strategies for a given distributed system.
• systematically analyze distributed, networked systems and feedback the analysis results into an efficient, fault-tolerant system design

Type of instruction

Types of instruction are listed at the start of §17; Structure and contents of the programme.

Exam

Exams