FI:PB165 Graphs and networks - Course Information
PB165 Graphs and networks
Faculty of InformaticsAutumn 2013
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Luděk Matyska, CSc. (lecturer)
doc. RNDr. Eva Hladká, Ph.D. (lecturer)
doc. Mgr. Hana Rudová, Ph.D. (lecturer)
Ing. Eva Výtvarová (assistant) - Guaranteed by
- doc. RNDr. Vlastislav Dohnal, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics - Timetable
- Tue 12:00–13:50 G126
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Informatics (programme FI, B-AP)
- Bioinformatics (programme FI, B-AP)
- Economic Information Systems (programme ESF, B-SI)
- Informatics with another discipline (programme FI, B-EB)
- Informatics with another discipline (programme FI, B-FY)
- Informatics with another discipline (programme FI, B-IO)
- Informatics with another discipline (programme FI, B-MA)
- Informatics with another discipline (programme FI, B-TV)
- Public Administration Informatics (programme FI, B-AP)
- Mathematical Informatics (programme FI, B-IN)
- Parallel and Distributed Systems (programme FI, B-IN)
- Computer Graphics and Image Processing (programme FI, B-IN)
- Computer Networks and Communication (programme FI, B-IN)
- Computer Systems and Data Processing (programme FI, B-IN)
- Programmable Technical Structures (programme FI, B-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (programme FI, N-AP)
- Social Informatics (programme FI, B-AP)
- Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
- Course objectives
- The lecture provides basic information about graphs and graph algorithms, used in the computer networks. Special emphasis is taken to present planning and scheduling as specific graph problems, as well as the load distribution problem in distributed systems.
Graduate will be able to explain several graph algorithms and their use in computer systems and networks.
Graduate will be able to analyze particular problem and transform it into appropriate graph representation.
Graduate will be further able to analyze and solve simple scheduling and planning problems.
Graduate will be able to solve simple graph problems.
Graduate will be able to interpret computer network behavior in terms of graph theory. - Syllabus
- Graph and computer networks, trees, root trees, binary trees.
- Graph searching. Spanning tree algorithms. Shortest path.
- Planning and scheduling problems and their graph representation.
- Project scheduling and critical path method.
- Graph colouring and timetabling.
- Data transfer planning.
- List scheduling, mapping heuristics, clustering.
- Load balancing.
- Switching and routing algorithms, GMS networks planning, peer to peer networks.
- P2P networks, problem od adding and deleting node, routing.
- Graphs for modeling and simulation Internet type networks.
- Network Coding.
- Literature
- Kocay, William. Graphs, algorithms, and optimization. Chapman \& Hall/CRC Press, 2005.
- GIBBONS, Alan. Algorithmic graph theory. Cambridge: Cambridge University Press, 1994, ix, 259. ISBN 0521288819. info
- PLESNÍK, Ján. Grafové algoritmy. 1. vyd. Bratislava: Veda, 1983, 343 s. info
- PINEDO, Michael. Planning and Scheduling in Manufacturing and Services. Springer, 2005. Springer Series in Operations Research. info
- Teaching methods
- Standard lecture, no drills, no homeworks. Lectures include exercises.
- Assessment methods
- Midterm written exam, this result is 20% of the final evaluation. Final written exam (9 questions, 100 points) is 80% of the final evaluation. For completion of a course, it is necessary to have base knowledge from all three areas of the course -- base graph algorithms, planning and scheduling in graphs and networks, graph algorithms in computer networks. Evaluation is A 100%-90%, B 89%-80%, C 79%-70%, D 69%-60%, E 59%-55%.
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Autumn 2013, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2013/PB165