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Computer Networks

Code: 102746
Credits: 6
2026/2027
Degree programme Type Course
Computer Engineering OB 2

Contact lecturer

Name :
Sergi Robles Martinez
Email :
sergi.robles@uab.cat

Teaching staff

Carlos Garrigues Olivella
Juan Antonio Martinez Carrascal
Josep Prieto Blazquez

Group languages

You can consult this information at the end of the document.

Prerequisites

There are no prerequisites. However, students should be familiar with the most basic concepts of Operating Systems. It is also recommended for students to have taken the courses on basic programming.

In case of discrepancies between the versions of this guide in different languages, the Catalan version shall prevail.

Objectives

The formative objectives of the course are, on the one hand, that students get a general vision of the concepts related to computer networks and with the interconnection of heterogeneous networks; that they thoughfully know the issues and protocols related with the joint operation of heterogeneous systems over a set of interconnected networks and the main distributed application in these systems, with a notion of their development. On the other hand, students have to be able to design extensible and robust internet networks, to configure connections to internet networks, and to detect and solve network problems due to missconfigurations or protocol attacks.

Learning outcomes

  • CM21 (Build IT projects that use different technological infrastructures in accordance with the principles of quality, reliability, IT security and cost.) Build IT projects that use different technological infrastructures in accordance with the principles of quality, reliability, IT security and cost.
  • KM24 (Explain the basic principles of computer structure, operating systems, IT networks, the Internet and storage systems.) Explain the basic principles of computer structure, operating systems, IT networks, the Internet and storage systems.
  • SM28 (Analyse technological infrastructures in any field of computer engineering to assess their economic, social and environmental impact aimed at implementing and continuously improving them to ensure their reliability, safety and quality.) Analyse technological infrastructures in any field of computer engineering to assess their economic, social and environmental impact aimed at implementing and continuously improving them to ensure their reliability, safety and quality.
  • SM29 (Apply knowledge of IT system interconnection to solve computer engineering problems.) Apply knowledge of IT system interconnection to solve computer engineering problems.
  • SM30 (Apply knowledge of operating systems, distributed systems, computer networks and the Internet to develop IT systems, services and applications.) Apply knowledge of operating systems, distributed systems, computer networks and the Internet to develop IT systems, services and applications.

Contents

Unit 1. Introduction

  • Computer networks and network of networks
  • The TCP/IP protocol family
  • Basic networks typologies and technologies

Unit 2. Netork interconnection protocols

  • Principles of network interconnection
  • Addressing
  • Local address resolution
  • IP protocol
  • Basic routing
  • ICMP Protocol

Unit 3. End-to-end protocols

  • Principles of end-to-end communications
  • User Datagram Protocol UDP
  • Reliable byte stream protocol TCP

Unit 4. Apploication protocols

  • Principles of TCP/IP applications
  • Application access to lower layers. Socket of Berkeley interface
  • Domain Name System DNS
  • Configuration Protocol DHCP

Unit 5. Advanced protocols for network interconnections

  • Internet architecture
  • Autonomous Systems and Neutral Points
  • Routing protocols within Autonomous Systems (RIP, OSPF)
  • Routing protocols between Autonomous System (BGP)

Learning activities and methodology

Title Hours ECTS Learning outcomes
Laboratory sessions 12 0.48
Supervised activities proposed in class 8 0.32
Problem resolution sessions 12 0.48
Course problems writing 30 1.2
Theory classes 26 1.04
Preparation and autonomous work for the laboratory sessions 24 0.96
Study and preparation for the assessment tests 30 1.2

Throughout the course, the following learning activities will be carried out:

  • Theory sessions, in which the instructor will provide students with the theoretical foundations of the course, as well as strategies for acquiring, expanding, and organizing this knowledge. Active student participation will be encouraged, for example through discussions on topics for which multiple technological solutions are possible.
  • Problem-solving sessions, in which students will actively participate in consolidating the knowledge acquired by solving, presenting, and discussing problems related to the course content. A distinction is made between problems and exercises, the latter being considered relatively straightforward. Problems will often admit multiple valid solutions and may give rise to discussion among students.
  • Laboratory sessions, in which students, working in groups, will be challenged with small practical tasks to analyze and solve. These sessions will have been designed, documented, and prepared in advance by the instructor. Students are expected to prepare for each laboratory session by reviewing the relevant theoretical concepts and the basic technical aspects required for the proposed activities. The laboratory sessions are intended to help students develop the practical skills associated with the course and contribute to the achievement of specific learning outcomes and competencies.
  • Individual assignments, consisting of exercises related to the theory and problem-solving sessions, to be completed individually at different points throughout the semester.
  • Supervised activities, conducted throughout the course under the guidance of the instructors, aimed at consolidating students’ understanding of the course material and exploring its practical applications.

No differentiated arrangements are planned for students who are repeating the course.

The UAB Virtual Campus (Moodle) will be used as the primary platform for communication between students and instructors, as well as among students. It will also be used for the submission of assignments and for providing access to the course materials.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Activities 10%. No minimum mark is required for this part 2 0.08 KM24, SM29, SM30
Knowledge and skill deliverable exercises 15%. The minimum required grade for this component is 0.1 out of 10. 0.5 0.02 CM21, KM24, SM29
Practical laboratory session follow up, with the possibility of undertaking a test during the session 10%. The minimum mark required by this part is 5 out of 10 2 0.08 SM28, SM29, SM30
Practical case 5%. A minimum mark of 0.1 over 10 is required for this part 0.5 0.02 CM21, KM24, SM28, SM29, SM30
Final validation test 40%. The minimum grade required by this part is 5 out of 10 2 0.08 KM24, SM29, SM30
Assessment of skills acquired in the laboratory challenges 20%. The minimum mark required by this part is 4 out of 10 1 0.04 CM21, SM28, SM29, SM30

Assessment Criteria


Assessment is continuous and formative and is based on the evidence of learning generated by students through in-class participatory activities, individual assignments, final examinations assessing knowledge acquisition, and examinations assessing laboratory work.


Assessment activities and instruments

In-class activities

These activities are carried out during theory and problem-solving sessions and are scheduled irregularly throughout the semester. Since they take place during face-to-face sessions, participation is not mandatory (i.e., they are not required to pass the course, although they contribute to the final grade). Examples include: commenting on a short documentary shown in class, describing a role-playing activity conducted during a session, completing multiple-choice questions on the theory or problem-solving session just completed, analyzing the operation of a routing information exchange protocol, etc.

Individual assignments and final examinations assessing knowledge and skills

The individual assignments are written assessments designed to evaluate whether each student is progressively acquiring the knowledge and skills covered up to that point in the course. These assignments do not exempt students from any part of the final examination, and a minimum grade of 0.1/10 is required.

The final examinations assessing knowledge and laboratory work are individual written examinations intended to verify that each student has achieved the minimum required knowledge, skills, and competencies of the course. These examinations reflect the importance placed on ensuring that students attain the knowledge, skills, and competencies expected in an engineering degree. Passing both the final knowledge examination and the laboratory assessment examinations is mandatory in order to pass the course.

Practical case study

Students will complete an individual practical case study in which they will apply the competencies acquired throughout the course. This assessment evaluates the student’s ability to integrate the knowledge and skills learned during the course in order to solve a realistic scenario similar to those that may be encountered in their future professional career.

Laboratory sessions

Laboratory work consists of a series of structured laboratory sessions in which student teams solve predefined challenges designed to develop course-specific knowledge, skills, and competencies. Detailed information regarding the organization of the laboratory sessions (challenges, groups, schedule, grading, etc.) and their assessment (reports, attendance requirements, etc.) will be available on the Virtual Campus. Attendance at laboratory sessions is mandatory. To be eligible for assessment, students must attend at least 80% of the laboratory sessions. Assessment of specific laboratory sessions may be rescheduled only with prior authorization from the Academic Administration Office (for example, in cases of medically justified absence). At the end of each laboratory session, students will complete an individual written assessment to validate the achievement of the corresponding learning outcomes. Passing these assessments is required in order to pass the course.


Assessment criteria

For problem-solving activities and supervised work, assessment will consider individual commitment, cooperation within the group, the quality of the work produced, and the student’s level of participation across the different assessment activities. Quality indicators include the correct use of technical terminology, appropriate written expression, and the logical organization of the submitted work. Consistency and regular engagement throughout the course will also be taken into account. Solutions to problems are expected to be well justified and, where appropriate, properly revised.

For in-class activities, assessment will be based on student participation and any reports or documents submitted.

For the laboratory component, assessment will consider active participation during the laboratory sessions and performance in the final laboratory assessments.

For the individual assignments and the final examinations assessing knowledge and laboratory work, the primary assessment criterion will be the correctness of the answers provided.


Academic integrity: plagiarism, cheating, and other irregularities

Without prejudice to any additional disciplinary measures that may be deemed appropriate, and in accordance with the current academic regulations, any irregularity committed by a student that may affect the assessment of an activity will result in a grade of 0 (zero) for that activity. Assessment activities graded in this manner are not eligible for reassessment.

If passing the affected assessment activity is a requirement for passing the course, the student will automatically fail the course without the possibility of passing it through reassessment during the same academic year.

Irregularities include, but are not limited to:

  • copying all or part of a laboratory assignment, report, or any other assessment activity;
  • allowing another student to copy;
  • submitting group work (from the current or previous academic years) that has not been completed entirely by the members of the group (this applies to all group members, not only those who did not contribute);
  • submitting as one’s own work material produced by a third party, including translations or adaptations, or, more generally, work containing elements that are not original and exclusively produced by the student (for example, content generated using generative Artificial Intelligence tools such as Gemini, ChatGPT, Copilot, etc.);
  • having communication devices (such as mobile phones, smartwatches, smart pens with cameras, etc.) accessible during individual theory or practical examinations;
  • communicating with other students during examinations;
  • copying or attempting to copy from other students during examinations;
  • using or attempting to use notes or written materials related to the course content during examinations unless their use has been explicitly authorized.

In cases involving academic misconduct during an assessment activity, the final numerical grade recorded for the course will be the lower of 3.0 and the weighted average of the student’s grades. Consequently, it will not be possible to pass the course through compensation.

In future editions of the course, students who have committed academic misconduct during an assessment activity will not receive credit for any previously completed assessment activities.

In summary: copying, allowing others to copy, plagiarism, or attempting any of these actions in any assessment activity will result in a Fail, with no possibility of compensation or recognition of previously completed assessment activities.


Use of Generative Artificial Intelligence tools

This course acknowledges the increasing use of generative Artificial Intelligence as a support tool and therefore permits its use to a limited extent.

As a general rule, these tools may only be used to improve the formal aspects of a student’s work, such as writing quality, style, clarity of presentation, language revision, translation, or to obtain occasional assistance with technical issues.

The use of generative Artificial Intelligence to produce content that is subject to assessment is not permitted. This includes, but is not limited to, methodological design, system design, experimental work, analysis or interpretation of results, idea generation, or the formulation of conclusions. These tasks must be carried out entirely by the student, as they constitute the essential intellectual and creative work required to pass the course. Given the diversity of assessment activities, students should consult the course instructor whenever they are uncertain about the permitted use of these tools.

In all cases, students must explicitly state, in every submission uploaded to the Virtual Campus, whether generative Artificial Intelligence tools have been used, specifying which tools were used, for what purpose, and to what extent.

Irresponsible, excessive, or unnecessary use of these tools will negatively affect the assessment. Failure to disclose their use, or inappropriate use of such tools, may result in failing the course.


Final grade

The final course grade, which reflects the acquisition of knowledge, skills, and competencies, will be calculated as the weighted average of the following components:

  • 40% – Final knowledge examination. Minimum required grade: 5.0/10.
  • 15% – Individual assignments. Minimum required grade: 0.1/10.
  • 5% – Practical case study. Minimum required grade: 0.1/10.
  • 10% – In-class activities. No minimum grade required.
  • 10% – Laboratory coursework. Minimum required grade: 5.0/10.
  • 20% – Laboratory skills assessment. Minimum required grade: 4.0/10.

The combined grade corresponding to the individual assignments (15%) and the practical case study (5%), hereafter referred to as ESP, will be adjusted according to the student’s grade in the final knowledge examination. If the ESP grade is 1.5 or higher and the grade in the final knowledge examination is 5.0 or higher, the ESP grade used in the final calculation will be the greater of 5.0 and the original ESP grade. This adjustment reflects the fact that the final knowledge examination assesses the complete theoretical content of the course.

If a student does not pass the course because one or more assessment components do not reach the required minimum grade, the final numerical grade recorded will be the lower of 4.0 and the weighted average of all assessment components.

Students who do not participate in any assessment activity will receive the grade Not Assessed.

As indicated above, in cases of academic misconduct, the final numerical grade recorded will be the lower of 3.0 and the weighted average of the student’s grades.

Honours Distinction (Matrícula d’Honor) will be awarded taking into account active participation throughout the course (for example, contributing to problem solving in the course discussion forum), additional non-assessed merits announced during the semester (such as optional challenges), the final course grade, and the grade obtained in the final knowledge examination.

Only students who have not participated in any assessment activity will receive the grade Not Assessed.


Assessment schedule

  • Throughout the semester: in-class activities and laboratory sessions, together with their corresponding assessments.
  • During laboratory sessions: assessment of laboratory coursework.
  • Throughout the semester: individual assignments and the practical case study.
  • At the end of the semester: final knowledge examination and laboratory skills assessment.

Assessment dates will be published on the Virtual Campus and may be modified if necessary due to scheduling adjustments or unforeseen circumstances. Any changes will always be announced through the Virtual Campus, which is considered the official communication channel between instructors and students.

Students who do not pass the final knowledge examination or the laboratory skills assessment at the first attempt will have the opportunity to take a reassessment examination.

Reassessment is not available for in-class activities, individual assignments, the practical case study, or laboratory coursework, as these are integral components of the continuous assessment process and cannot be meaningfully reproduced outside the period in which they take place.

Students are entitled to review all assessed activities.


Recognition of previous assessment activities

No automatic recognition of previously completed assessment activities will be granted, and students repeating the course will not receive any differentiated treatment.

Requests for recognition of previous assessment activities must be submitted explicitly following the procedure that will be explained on the first day of class.


Single assessment

This course cannot be assessed through the University’s single assessment procedure.

Bibliography

Core bibliography:

  • D. E. Comer (2021). Internetworking with TCP/IP. 7th Edition. Pearson.
  • J. F. Kurose, K. W. Ross (2021). Computer Networking: A Top-Down Approach. Pearson.

Recommended bibliography:

  • G. Tomsho (2025). Guide to Networking Essentials. 9th Edition. Cengage.
  • W. R. Stevens (2011). TCP/IP Illustrated, Volume I. 2nd Edition. Addison-Wesley.
  • A. S. Tanenbaum (2021). Computer Networks. 6th Edition. Pearson.
  • W. Stallings (2020). Data and Computer Communications. 11th Edition. Pearson.
  • M. Hernández. Computer Networks and Internet: A Study Guide. https://github.com/miguelinux314/uab-xoi/blob/master/main.pdf

Web resources:

  • UAB Virtual Campus (Moodle): https://cv.uab.cat


Software

This course will only use free software, such as the GNU/Linux operating system.

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 41 English second semester morning-mixed
(TE) Theory 43 Catalan second semester morning-mixed
(TE) Theory 45 Catalan/Spanish second semester afternoon
(TE) Theory 47 Catalan/Spanish second semester morning-mixed
(PAUL) Classroom practices 411 English second semester morning-mixed
(PLAB) Practical laboratories 411 English second semester morning-mixed
(PAUL) Classroom practices 412 English second semester morning-mixed
(PLAB) Practical laboratories 412 English second semester morning-mixed
(PLAB) Practical laboratories 413 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 414 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 415 English second semester morning-mixed
(PLAB) Practical laboratories 416 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 417 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 418 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 419 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 420 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 421 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 422 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 423 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 424 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 425 Catalan/Spanish second semester morning-mixed
(PAUL) Classroom practices 431 Catalan second semester morning-mixed
(PAUL) Classroom practices 432 Catalan second semester morning-mixed
(PAUL) Classroom practices 451 Catalan/Spanish second semester morning-mixed
(PAUL) Classroom practices 452 Catalan/Spanish second semester morning-mixed
(PAUL) Classroom practices 471 Catalan/Spanish second semester morning-mixed