Performance Evaluation of Computer Systems and Networks

Teachers

• Prof. Giovanni Stea
• Ing. Giovanni Nardini

Course syllabus

• Probability theory and statistics (~30 h):
  • Fundamental definitions and theorems on probability. Uniform probability model. Discrete and continuous random variables. Notable RV distributions (exponential, uniform, Poissonian, normal, binomial, chi-square, student-t etc.). Central limit theorem.
  • Sample and population: estimators and confidence intervals. Data analysis and summarization. Model fitting, experiment design.
• Simulation (~30 h):
  • Principles of discrete event simulation: events, event queues, random number generation, structure of a simulation software.
  • Description of the general-purpose OMNeT++ simulation framework. Hands-on experiments with the OMNeT++ framework.
  • Simulation workflow: system modeling, experiment planning, factor reduction, independent replications, transient and steady-state behavior, output data analysis, experiment automation.
• Analytical System modeling (~30 h):
  • Queueing Theory: definition of stochastic process. Markov processes. Continuous-tmie Markov Chains.
  • Average measures: number of clients, waiting and queueing time. Little's theorem. PASTA theorem and the importance of the viewpoint.
  • Single-queue systems: M/M/1, M/M/c, M/M/1/k, discouraged arrivals, finite populations, batch arrivals and services.
  • Network of queues: open and closed networks. Jackson's networks. Gordon and Newell's networks. Buzen's algorithm.

Teaching material

Slides and exercises will be made available in the course channel on the Microsoft Teams platform.
The OMNeT++ Simulation manual can be found here.

Tools

In order to do exercises during labs and the group simulation project, students are required to install the OMNeT++ software on their computer (works on Windows, Linux and MacOS).
OMNeT++ can be downloaded from here. A detailed install guide is available here.