First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
Course unit
INP9086631, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course Second cycle degree in
IN2371, Degree course structure A.Y. 2019/20, A.Y. 2019/20
bring this page
with you
Degree course track INTERNATIONAL MOBILITY [005PD]
Number of ECTS credits allocated
Type of assessment Mark
Course unit English denomination NETWORK SYSTEMS (I.C.)
Department of reference Department of Information Engineering
Mandatory attendance No
Language of instruction English
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge TOMASO ERSEGHE ING-INF/03

Modules of the integrated course unit
Course unit code Course unit name Teacher in charge

Course unit organization
Teaching method frontal

Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2019 course timetable

Examination board
Examination board not defined

Prerequisites: This course has the following prerequisites: knowledge in Probability Theory, and Computer Programming in any language which is appropriate for network analysis (e.g., MatLab, Python, C, Java, Linux). Moreover: 1. for the INTERNET module: to be familiar with the most basic networking and communication concepts and terms (ISO/OSI model, packet-based networks, routing); 2. for the NETWORK SCIENCE module: knowledge in Calculus and Linear Algebra; any further knowledge of networking processes in economics, biology, telecommunications, semantics, etc. might be useful.
Target skills and knowledge: The course is expected to provide the following knowledge and skills:

INTERNET module:
1. To know and understand the architecture of the Internet
2. To know the characteristics of the different types of data sources and their mathematical modeling
3. To understand the main protocol design principles
4. To know and understand the operating principles of the main network protocols (MAC, DLL, IP, UDP, TCP, FTP, HTTP)
5. To understand the role and functioning of the fundamental elements of the Internet, such as NAT, DHCP, DNS, SMPT servers
6. To master the mathematical tools need to dimension a simple communication network and evaluate its performance
7. To be able to set up and run a simple local network
8. To become familiar with fundamental tools for network configuration and diagnostics (packet sniffer, Tcpdump, ping, iperf, ifconfig,...)

1. To learn and critically interpret the main network analytic measures
2. To be aware of the main mathematical models describing network generation processes
3. To be able to rank nodes in a network according to their level of importance
4. To identify communities (i.e., tightly-knit groups), even partially overlapping, using proper algorithms
5. To evaluate the level of robustness/cohesion of a network
6. To know the main scenarios of application, possibly in cross-disciplinary contexts, of the techniques studied
7. To be able to summarise the analysis of a network in a professional paper
8. To be able to implement computer algorithms for network analysis
Examination methods: The course has the following methods of examination:

INTERNET module:
The final exam will be the same for both ATTENDING and NON-ATTENDING students since it does not rely on in-class activities. The exam consists of two parts, namely: 1. a WRITTEN EXAM at the computer, 2. a LAB TEST. Students will be offered four attempts to pass the written and the lab tests. During in-class lectures, the students may be offered to participate to some (in class or at home) activities, such as peer-reviewing of other students' reports, participating in-class discussion and taking part to problem-solving competitions. The active participation to such initiatives may bring a few extra points (up to 3) to the students.

The verification of the expected knowledge and skills is carried out with the DEVELOPMENT OF A PROJECT aimed at verifying the ability to apply theory in interdisciplinary contexts, and which requires: the choice, the collection of data, and the analysis of a different network for each student; computer implementation (in any programming language known to the student) of the algorithms required for the analysis; the drafting of an essay. The project is foreseen in two ways: 1. for ATTENDING students in which the students are guided towards intermediate project objectives (HOMEWORKS) coherently with the development of the lessons, and complete the project at the end of the course; 2. for NON-ATTENDING students, in which the development of the project takes place in a single solution and is discussed in an oral exam in one of the four institutional dates. A bonus of up to 3 points is available for attending students that take part to an INTERDISCIPLINARY PROJECT with social science students attending the twin course on SOCIAL NETWORK ANALYSIS.

The final grade is expressed as a combination of the judgments in the two modules (50%+50%).
Assessment criteria: The evaluation criteria with which the verification of knowledge and expected skills will be carried out will be:

INTERNET module:
1. Completeness of the acquired knowledge
2. Level of understanding of the design principles of network protocols
3. Ability to discuss the pros and cons of the different network protocols
4. Ability to dimension a network through the proposed techniques
5. Knowledge of the technical terminology
6. Competence and coherence in the interpretation of performance curves and traces generated by network analytics tools
7. Capability of applying the learned knowledge to network problems other than those addressed in the course
8. Level of familiarity with basic network configuration and management tools

1. Completeness of the acquired knowledge
2. Ability to analyse a network through the proposed techniques
3. Property in the technical terminology used, both written and oral
4. Originality and independence in the identification of the network under study
5. Competence and coherence in the interpretation of the meaning of the obtained analytical measures
6. Ability in the use of IT tools in the study of network analytical measures.

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Case study
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • One Note (digital ink)
  • Latex
  • Matlab

Sustainable Development Goals (SDGs)
Quality Education Gender Equality Industry, Innovation and Infrastructure Reduced Inequalities