Network Performance and Traffic

Course Description

Analysis and modeling of network traffic at packet and flow level, metrics for network performance, introduction to queuing theory, application of queuing theory to computer networks, Markov processes and their use in computer network modeling, flow and congestion control, optimal routing, tools for performance analysis and modeling in networks, network calculus fundamentals.

Learning Outcomes

  1. Understand and explain basic metrics for network performance
  2. Understand and explain the basics of queuing theory
  3. Know how to apply queuing theory in network analysis and modeling
  4. Understand and explain Markov processes
  5. Be able to apply knowledge of Markov processes in network analysis and modeling
  6. Be able to use tools to analyze the performance of communications networks
  7. Know the procedures for modeling network traffic
  8. Be able to optimize routing of network traffic flows

Forms of Teaching

Lectures

Theoretical lectures with teaching practical tools as well

Independent assignments

Homework in which it is necessary to make a practical part and write a report

Laboratory

Group project

Other

The course is taught through lectures, homework, and laboratory exercises. Lectures are three hours per week. For each lecture, students should prepare and read the assigned literature that is discussed during the first hour. During the class the tasks are also solved. Students are tasked to do a practical part presented in a lecture within four homework assignments. Furthermore, students have a group project. In a group project, they should apply the theoretical knowledge gained in the lecture. In this approach, theoretical knowledge should be applied twice, first in the course of homework (structured application) and second in the project (free application).

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 0 % 10 % 0 % 0 %
Homeworks 0 % 10 % 0 % 0 %
Class participation 0 % 10 % 0 % 0 %
Mid Term Exam: Written 50 % 35 % 0 %
Final Exam: Written 50 % 35 %
Exam: Written 50 % 35 %
Exam: Oral 35 %
Comment:

Homework, laboratory and activity are calculated in case of written and oral exam.

Week by Week Schedule

  1. Architectures and technologies of today's networks
  2. Network traffic in packet networks at the packet, burst and flow level. Metrics for describing network traffic performance.
  3. Approaches to network traffic modeling
  4. Introduction to queueing theory
  5. Application of queueing theory in computer networks
  6. Network monitoring - principles and tools.
  7. Network flow monitoring - Netflow, IPFIX, sFlow
  8. Midterm exam
  9. QoS and QoE. Quality assurance mechanisms in networks. Service level agreement. Regulation in the field of traffic management.
  10. Netowkr management - FCAPS model.
  11. Evolution of network management protocols. SNMP, YANG, NETCONF protocols
  12. Network management in SDN.
  13. Service configuration and inventory management.
  14. Performance analysis of local area networks, Performance analysis of wireless networks, Data link layer performance analysis
  15. Final exam

Study Programmes

University graduate
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Electronics (profile)
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Information and Communication Engineering (profile)
Elective Courses of the Profile (2. semester) Free Elective Courses (2. semester)
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Core-elective courses (2. semester)
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Free Elective Courses (2. semester)
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Theoretical Course (2. semester)

Literature

(.), J.N. Daigle (2005.), Queuing Theory with Applications to Packet Telecommunication, Springer,
(.), T.G. Robertazzi (2000.), Computer Nertworks and Systems: Queueing Theory and Performance Evaluation?, 3rd ed., Springer,
(.), H. Kobayashi, B.L. Mark (2009.), System Modeling and Analysis: Foundations of System Performance Evaluation, Pearson-Prentice Hall,
(.), D. Gross, J.F. Shortle, J.M. Thompson, C.M. Harris (2008.), Fundamentals of Queueing Theory, 4th ed., Wiley, New York,
(.), Skripta iz teorije prometa,

For students

General

ID 222477
  Summer semester
5 ECTS
L0 English Level
L1 e-Learning
30 Lectures
15 Laboratory exercises

Grading System

90 Excellent
80 Very Good
65 Good
50 Acceptable