Performance Evaluation of Computer Systems and Networks

(Subjects are not necessarily in order of presentation).

• Probability theory and statistics (~40 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 (~25 h):
• Principles of discrete event simulation: events, event queues, random number generation, structure of a simulator 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.
• Queueing Theory (~25 h):
• Queueing theory: Markov Property, Poisson processes, birth/death systems. Transient and steady-state solutions. Single-queue systems, open and closed queueing networks. Classed networks. Processor-sharing systems.

Students will also be requested to prepare a term project, consisting of both documentation and code, related to modeling and simulative performance analysis of a system.

Reference textbooks:

• S.M. Ross “Introduction to Probability and Statistics for Engineers and Computer Scientists”, Elsevier
• R. Jain “The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling”
• L. Kleinrock, Queueing Systems, vol. 1, Wiley

• J.Y. Le Boudec “Performance Evaluation of Computer and Communication Systems”, EPFL
• D.A. Menascé et al. “Performance by Design”, Prentice Hall
• A.M. Law, W.D. Kelton “Simulation Modeling and Analysis”, McGraw-Hill
• S.M. Ross, "Introduction to Probability Models", Elsevier