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Course: 2021/2022

Operating systems design

(13889)

Bachelor in Computer Science and Engineering (2011 Study Plan) (Plan: 256 - Estudio: 218)

Coordinating teacher: GARCIA GUZMAN, JAVIER

Department assigned to the subject: Computer Science and Engineering Department

Type: Compulsory

ECTS Credits: 6.0 ECTS

Course: 3º

Semester: 2º

Requirements (Subjects that are assumed to be known)

* Programming (Year 1 / Semester 1) * Software Development (Year 2 / Semester 2) * Operating Systems (Year 2 / Semester 2)

Objectives

The goal of this course is to introduce students into the organization, structure and internal vision of the operating systems necessary for Internet of Things systems. Students will learn the services that integrate sensor and actuator based systems and understand the influence that design decisions have on the behavior of an Internet of Things System. In order to archive this goal, the student have to acquire several generic skills, knowledge, capacities and attitudes. General/transversal competences: - Analysis and synthesis capacities - Abilities to organize and to plan - Problem resolution abilities - Capacity to apply theoretical concepts Specific competences: - Cognitive (knowledge) 1. Know the different types of devices and operating systems of an Internet of Things System. 2. Know different types of use and applications of IoT technology in today's society. 3. Know the structure of an Embedded Operating System that allows the operation of sensors and actuators to be controlled. 4. Know the criteria for selecting the Embedded Operating Systems necessary to control sensors and actuators. 5. Know the programming interfaces (APIs) that embedded systems provide to customize the operation of sensors and actuators. 6. Know the fundamentals for programming IoT devices through the APIs provided by the Embedded Operating Systems. 7. Know operating systems and base platforms to manage clouds of IoT devices. 8. Know the fundamentals of operating systems to package and virtualize microservices to manage clouds of IoT devices. - Procedimental/Instrumental (Know how) 1. Configure the Hardware and Operating System that controls the operation of sensors and actuators 2. Program the basic operation of IoT devices using the APIs provided by the Operating System. 3. Program basic microservices for IoT device cloud management 4. Virtualize microservices to manage IoT device clouds - Attitudinal (To be) 1. Critical attitude towards the internal architecture of current IoT systems. 2. Concern for the quality of the components of an IoT system. 3. Motivation for archiving better solutions. 4. Self-learing capacities.

Skills and learning outcomes

Link to document

Description of contents: programme

1. IoT Systems Architecture 2. Sensors and Actuators 3. Embedded Operating Systems for IoT devices 4. Fundamentals of programming IoT Devices 5. IoT Edge to Cloud Protocols 6. Microservices for IoT Devices Cloud Management 7. Packaging and deployment of microservices for IoT

Learning activities and methodology

- Lectures - Practical lessons - Guided Exercises, Challenges and Exams - Student's work Relationship between outcomes and evaluable activities: CB4: Practical classes, practical workbooks and final challenge. CG9: Practical classes, practical workbooks and final challenge. CGB4: Theory classes, practical classes, exams, workbooks and final challenge. CB5: Theory classes, practical classes, exams, workbooks and final challenge. CGO4: Theory classes, practical classes, exams, workbooks and final challenge. CGO6: Practical classes, practical workbooks and final challenge. CECRI 10: Theory classes, practical classes, exams, workbooks and final challenge. CECRI 11: Theory classes, practical classes, exams, workbooks and final challenge. Soft-skills: work in groups

Assessment System

ORDINARY CALL
The continuous evaluation is made up of: Notebooks of Practical Exercises, Challenges and, exceptionally, partial theory exams.

Regarding continuous evaluation:
  + All practical exercise books and challenges must be delivered
     * The average mark of the practices and challenges must be greater than or equal to 5 out of 10.
  + Exceptionally, the final exam of the subject may be replaced by partial exams
     * The average grade of the partial exams must be greater than or equal to 5 out of 10.

The final exam:
  + Includes all the content and aspects of the subject.
  + The final exam has a minimum grade of 5 out of 10.

The grade of the subject (by following the continuous evaluation) is calculated as follows:
    Final grade = Final exam grade * 0.30 + Practical exercises notebooks * 0.40 + Final challenge * 0.3

Alternatively, the final exam will represent 60% of the grade and the Final Challenge 40%,
for all those students who do not join the previous continuous assessment system.
The minimum grade of each of the parts must be equal to or greater than 5 out of 10.

EXTRAORDINARY CALL
The final exam will represent 60% of the grade and the Final Challenge 40%.
The minimum grade of each of the parts must be equal to or greater than 5 out of 10.

CLARIFICATIONS
1) Cheating programming assignments, lab assignments, etc. will be prosecuted. Not only the continuous evaluation is lost but further punishment actions will be taken. Both, copying from other group or copying from Internet works are considered cheating.
2) For all group works, the related skills and abilities must be fulfilled by all members. All members share the responsibility for the submitted work.
3) Depending on the total number of students, the academic calendar, number of groups, etc., some adaptations will be necessary in order to unwrap the course. Aula Global will be used to introduce the supplementary norms to the ones introduced here.
4) In order to obtain the best possible grade, not only academic aspects will be considered but also how the student has been collaborating in the general learning process of the course.

% end-of-term-examination 30
% of continuous assessment (assigments, laboratory, practicals...) 70

Calendar of Continuous assessment

Basic Bibliography

Anand Tamboli. Build Your Own IoT Platform: Develop a Fully Flexible and Scalable Internet of Things Platform in 24 Hours. Apress. 2019
Bob Familiar. Microservices, IoT, and Azure: Leveraging DevOps and Microservice Architecture to Deliver SaaS Solutions. Apress. 2015
Gabriel N. Schenker, Hideto Saito, Hui-Chuan Chloe Lee, Ke-Jou Carol Hsu. Getting Started with Containerization. Packt Publishing. 2019
Perry Lea. Internet of Things for Architects. Packt Publishing. 2018
Peter Waher. Mastering Internet of Things. Packt Publishing. 2018
Qusay F. Hassan. Internet of Things A to Z. Wiley-IEEE Press. 2018
Richard Blum, Christine Bresnahan. Sams Teach Yourself Python Programming for Raspberry Pi in 24 Hours, Second Edition. Sams. 2015

The course syllabus may change due academic events or other reasons.