Lectures:
1. Theoretical basics
Requests, servers, queues, Kendall's notation
Modelling regarding time and modelling regarding the possible states of the system
Request arrival rate in request serving rate
Serving units (discrete, exponential, Erlang's, …),
Serving networks
Definition of simulation parameters (work-load, metrics, required resources, etc.)
Analysis and interpretation of simulation results
Petri nets, Coloured Petri nets
Performance metrics, latency
2. Practical use of theory presented
Modelling and simulation of networks
Modelling and simulation of protocols
Modelling and simulation of higher layer protocols and services
Tools for network modelling and simulation (OpNet, NS2, OMNeT++, TETCOS, GTNetS, etc.)
Laboratory courses:
Methods and approaches presented during the lectures will be demonstrated on practical computer network examples during the laboratory courses. Different software tools will be used such as OpNet, NS2, OMNeT++, TETCOS, GTNetS, etc.
Computer networks modelling
Miha Mraz
- N. C. Hock: Queueing Modelling Fundamentals, J.Wiley &, Sons, New York, 1996.
- M. E. Woodward: Communication and computer networks: modelling with discrete-time queues, Pentech Press, London 1993.
- M. Mraz, M. Moškon: Modeliranje računalniških omrežij. 1. izd. Ljubljana: Založba FE in FRI, 2012. ISBN 978-961-6209-80-9. https://ucilnica.fri.uni-lj.si/course/view.php?id=209. [COBISS-SI-ID 265042944]
Objective of the course is to present the basics in modelling and simulation of computer networks to the students of computer and information science. The course is based on the theory of service which acknowledges the students with the terms such as demands, serving units (resources), queues, bottlenecks etc. Students will learn the practical values of theoretical knowledge on the problems that arise in the field of computer networks.
Other competences:
Developing skills in critical, analytical and synthetic thinking.
Practical knowledge and skills of computer hardware, software and information technology necessary for successful professional work in computer and information science.
The ability to understand and solve professional challenges in computer and information science.
The ability to apply acquired knowledge in independent work for solving technical and scientific problems in computer and information science, the ability to upgrade acquired knowledge.
Knowledge and understanding:
Having the theoretical and methodological knowledge from the field modelling and simulations.
Understanding the importance of the field.
Application:
Application of methodological knowledge in design and support of various computer networks and their services.
Reflection:
Understanding the relations among theoretical knowledge and methodologies and practical problems from the field of computer networks.
Transferable skills – are not bound only to this course:
Students gain a new system perspective on the field of computer networks. This perspective opens new viewpoints such as data gathering and interpretation, problem identification and solving, critical analysis and synthesis.
Lectures and oral presentations of the subject. Seminal work on real-life examples and problems.
Continuing (homework, midterm exams, project work)
Final (written and oral exam)
grading: 5 (fail), 6-10 (pass) (according to the Statute of UL)
VASYLCHENKOVA, Anastasiia, MRAZ, Miha, ZIMIC, Nikolaj, MOŠKON, Miha. Classical mechanics approach applied to analysis of genetic oscillators. IEEE/ACM transactions on computational biology and bioinformatics, ISSN 1545-5963. [Print ed.], 2016, vol. , no. , str. 1-8, ilustr. [COBISS-SI-ID 1536851139]
BIZJAK, Manca, MRAZ, Miha, ZIMIC, Nikolaj, MOŠKON, Miha. Computational framework for modeling multiple noncooperative transcription factor binding and its application to the analysis of nuclear factor kappa B oscillatory response. Journal of computational biology, ISSN 1066-5277. [Print ed.], str. 1-11, ilustr. [COBISS-SI-ID 1536999619]
BORDON, Jure, MOŠKON, Miha, ZIMIC, Nikolaj, MRAZ, Miha. Fuzzy logic as a computational tool for quantitative modelling of biological systems with uncertain kinetic data. IEEE/ACM transactions on computational biology and bioinformatics, ISSN 1545-5963. [Print ed.], 2015, vol. 12, no. 5, str. 1199-1205, ilustr. [COBISS-SI-ID 1536282563]
MOŠKON, Miha, MRAZ, Miha. Systematic approach to computational design of gene regulatory networks with information processing capabilities. IEEE/ACM transactions on computational biology and bioinformatics, ISSN 1545-5963. [Print ed.], 2014, vol. 11, no. 2, str. 431-440, ilustr. [COBISS-SI-ID 10323028]
STRAŽAR, Martin, MRAZ, Miha, ZIMIC, Nikolaj, MOŠKON, Miha. An adaptive genetic algorithm for parameter estimation of biological oscillator models to achieve target quantitative system response. Natural computing, ISSN 1567-7818, Mar. 2014, vol. 13, no. 1, str. 119-127, ilustr. [COBISS-SI-ID 9950804]
