Queuing networks
Course: Systems and methods of decision making
Structural unit: Faculty of Computer Science and Cybernetics
Title
Queuing networks
Code
ДВВ.04
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
3
Learning outcomes
Know and understand the main sections and tasks of queuing networks, principles of analysis and modeling of queuing networks. Be able to use stochastic networks for mathematical modeling of real telephone and computer networks, development of nuclear physics and pharmacokinetics.
Form of study
Full-time form
Prerequisites and co-requisites
Know: basics of mathematical analysis, algebra, probability theory, mathematical statistics. Be able to: formalize tasks and compile algorithms for the implementation of tasks. Have basic skills: working with stochastic objects.
Course content
Gaining students basic knowledge of methods of accurate and approximate calculation of stochastic networks, solving optimization problems, skills to use stochastic networks for mathematical modeling of real telephone and computer networks, development of nuclear physics and pharmacokinetics.
Recommended or required reading and other learning resources/tools
1. Anisimov VV, Lebedev EA Stochastic service networks. Markov models: Textbook. allowance. - К .: Либідь, 1992. - 206 с.
2. Computer networks / Edited by Academician VM Glushkova. - М .: Связь, 1977. - 279 с.
3. Lebedev EA, Makushenko IA Risk Optimization for Multichannel Stochastic Networks: A Tutorial. - К .: НБУВ, 2007. - 65 с.
4. Vishnevsky MV Theoretical foundations of computer network design. - M .: Technosphere, 2003. - 512 p.
5. Lebedev EA, Makushenko IA Optimal external load distribution for multichannel stochastic networks: A textbook. - К .: НБУВ, 2012. - 90 с.
6. Kleinrock L. Computing systems with queues. - M .: Mir, 1979. - 600 p.
7. Burlakov MV Situational management in queuing systems. - К .: Наукова думка, 1991. - 160 с.
Planned learning activities and teaching methods
Lecture, test work, independent work.
Assessment methods and criteria
Test work, exam.
Language of instruction
ukrainian
Lecturers
This discipline is taught by the following teachers
Igor
Anatoliyovych
Makushenko
Applied Statistics
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
Applied Statistics
Faculty of Computer Science and Cybernetics