Subject description - B2M32DSA

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B2M32DSA Network Application Diagnostics Extent of teaching:2P + 2C
Guarantors:  Roles:PV,V Language of
teaching:
CS
Teachers:  Completion:Z,ZK
Responsible Department:13132 Credits:5 Semester:Z

Anotation:

The first part of the course deals with complex network structures, their characteristics identification, with recognition of both structural static and dynamic patterns, and anomaly detection. The second part of the course is focused on specification methods of static and dynamic behavior and their verification. The use of the methods is demonstrated on examples dealing with network application issues. The special treatment is dedicated not only to network and cloud applications, but also to posibilities of diagnostic process automation. The students gain sufficient skills in seminars where they solve practical problems in digital network domain.

Study targets:

The course introduces mathematical, theoretical, and practical foundations required for solving of diagnostic system problems that can be modelled using complex network structures.

Course outlines:

1. Introduction to diagnostics, testing, and verification of network applications.
2. Fundamental charakteristics of networks and models of random graphs.
3. Power distribution and preferential linking.
4. Network structure identification
5. Community detection
6. Ties prediction and network inference
7. Network dynamics and dynamic network processes
8. Specification system Alloy and its usage for network applications.
9. Dynamic behaviro specification using timed automata (system UPPAAL)
10. Specification and verification of protocols using system UPPAAL
11. Checking sequence of finite state machines
12. Finite state machine behavior identification
13. Tools for network testing and diagnostics, automation of processes
14. Diagnostics of network and cloud applications.

Exercises outline:

1. Student teams creation, development framework setting, basic libraries tutorial.
2. Variety type graph generation and path searching.
3. Rich club network nodes identification.
4. Computer communication network reconstruction.
5. Network partitioning and community detection
6. Communication patterns detection
7. Sensor network dynamic assessment.
8. Protocol specification and verification using Alloy.
9. Dynamic system specification using UPPAAL.
10. Protocol verification using UPPAAL.
11. State determination using special sequence of finite machines.
12. Finite machine reconstruction using active learning.
13. Test case design for multilayer network.
14. Seminar evaluation.

Literature:

- WWW http://alloy.mit.edu/alloy/ - WWW http://www.uppaal.org/ - Software Abstractions - Logic, Language, and Analysis. Jackson, D. MIT Press, 2006 - Networks: An Introduction, M. E. J. Newman, Oxford University Press (2010) - Networks, Crowds, and Markets: Reasoning about a Highly Connected World, Easley, D., Kleinberg, J.; Cambridge University Press, 2010

Requirements:

- Knowledge of linear algebra and graph theory. - Knowledge of network application and protocol fundamentals.

Webpage:

http://moodle.fel.cvut.cz

Keywords:

complex network, community detection, software specification, Alloy, UPPAAL, finite machine identification, diagnostics of network applications

Subject is included into these academic programs:

Program Branch Role Recommended semester
MPEK3_2016 Electronics V
MPEK4_2016 Media and Signal Processing V
MPEK2_2016 Radio and Optical Technology V
MPEK1_2016 Communication Systems and Networks PV 3


Page updated 16.12.2019 12:52:21, semester: Z,L/2020-1, L/2018-9, Z,L/2019-20, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)