Real Time Systems, 6 credits

Realtidssystem, 6 hp

TDDD07

Main field of study

Computer Science and Engineering Computer Science

Course level

Second cycle

Course type

Programme course

Examiner

Simin Nadjm-Tehrani

Director of studies or equivalent

Ola Leifler

Education components

Preliminary scheduled hours: 50 h
Recommended self-study hours: 110 h

Available for exchange students

Yes
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Period Timetable module Language Campus ECV
6CDDD Computer Science and Engineering, M Sc in Engineering 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CDDD Computer Science and Engineering, M Sc in Engineering 9 (Autumn 2018) 2 4 English Linköping, Valla E
6CDDD Computer Science and Engineering, M Sc in Engineering (Computer Systems Architecture) 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CDDD Computer Science and Engineering, M Sc in Engineering (International Software Engineering) 9 (Autumn 2018) 2 4 English Linköping, Valla E
6CDDD Computer Science and Engineering, M Sc in Engineering (System-on-Chip) 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CDDD Computer Science and Engineering, M Sc in Engineering (Systems Technology) 7 (Autumn 2018) 2 4 English Linköping, Valla C/E
6CMJU Computer Science and Software Engineering, M Sc in Engineering 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CMJU Computer Science and Software Engineering, M Sc in Engineering (International Software Engineering) 9 (Autumn 2018) 2 4 English Linköping, Valla E
6MDAV Computer Science, Master's Programme 1 (Autumn 2018) 2 4 English Linköping, Valla E
6MICS Computer Science, Master's Programme 1 (Autumn 2018) 2 4 English Linköping, Valla E
6MICS Computer Science, Master's Programme (Embedded Systems) 1 (Autumn 2018) 2 4 English Linköping, Valla E
6MELE Electronics Engineering, Master's Programme (System-on-Chip) 3 (Autumn 2018) 2 4 English Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Chinese 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - French 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - German 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Japanese 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Spanish 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CIII Industrial Engineering and Management, M Sc in Engineering 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CITE Information Technology, M Sc in Engineering 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CITE Information Technology, M Sc in Engineering (Computer Systems Architecture) 7 (Autumn 2018) 2 4 English Linköping, Valla E
6CITE Information Technology, M Sc in Engineering (International Software Engineering) 9 (Autumn 2018) 2 4 English Linköping, Valla E
6CITE Information Technology, M Sc in Engineering (Systems Technology) 7 (Autumn 2018) 2 4 English Linköping, Valla C/E

Main field of study

Computer Science and Engineering, Computer Science

Course level

Second cycle

Advancement level

A1X

Course offered for

  • Master's Programme in Computer Science
  • Electronics Engineering, Master's Programme
  • Computer Science and Engineering, M Sc in Engineering
  • Industrial Engineering and Management - International, M Sc in Engineering
  • Industrial Engineering and Management, M Sc in Engineering
  • Information Technology, M Sc in Engineering
  • Computer Science and Software Engineering, M Sc in Engineering

Specific information

Overlapping course contents: TDDA47, TDDB47, TDDC47, TTIT62.

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

First and second programming courses. A course on concurrent programming and operating systems.

Intended learning outcomes

After finishing this course the student is able to:

  • Choose, apply and implement CPU scheduling algorithms for hard real-time systems and their response time analysis, including mechanisms for sharing of multiple resources, and describe their relationship to deadlock avoidance.
  • Identify and analyze characteristics of real-time operating systems in terms of predictability compared to ordinary operating systems.
  • Explain implications of dependability requirements, identify and apply methods for fault tolerance in real-time systems development.
  • Describe and exemplify implications of predictability requirements for distributed real-time systems, and quality of service (QoS) requirements in soft real-time applications. Analysis of conflicting demands such as energy efficiency and responsiveness.
  • Analyze and implement methods for real-time communication in hard real-time applications, including event-triggered and time-triggered techniques.
  • Describe and exemplify design and modelling issues related to real-time systems.
  • Identify and model applications that require the use of real-time systems techniques and predict the outcomes for application of task/message scheduling and resource sharing methods.
  • Structure a real-time system and evaluate its performance based on application of different algorithms and methods.
  • Evaluate information from different research articles and books used as course material, and relate the information to the goals above.

 

Course content

Introduction to real-time systems applications. Resource allocation and in particular allocation of CPU as a resource (scheduling). Algorithms for static and dynamic scheduling: cyclic executive, rate-monotonic, earliest deadline first. Deadlock related problems in a real-time context and ceiling protocols for management of multiple resources. Overview of real-time operating systems. Dependability and its implications in real-time system development, fault tolerance, and exception handling. Interaction between resource allocation and performance demands in different systems, including approaches for assuring networked applications' quality of service (QoS), e.g. Intserv and Diffserv. Managing datacentre requirements with respect to energy efficiency and responsiveness. Design and application modelling in real-time systems. Distributed real-time systems and issues related to time, clocks and shared state. Real-time communication and support in time-triggered (TTP) and event-triggered (CAN) buses.

Teaching and working methods

The theory is presented during the lectures. Lessons help to solve exercises within the theoretical areas and prepare for the laboratory assignments. Resource sessions are used for discussing questions raised by students.

Examination

LAB1Laboratory work2 creditsU, G
TEN1Written examination4 creditsU, 3, 4, 5
Lab assignments lead to a written report within the group. Credit is given after a verbal examination of, and demonstration by, individual group members.

Grades

Four-grade scale, LiU, U, 3, 4, 5

Course literature

Articles and e-book chapters recommended on the course web pages.

Department

Institutionen för datavetenskap

Director of Studies or equivalent

Ola Leifler

Examiner

Simin Nadjm-Tehrani

Course website and other links

http://www.ida.liu.se/~TDDD07

Education components

Preliminary scheduled hours: 50 h
Recommended self-study hours: 110 h

Course literature

Books

  • Burns & Wellings, (2009) Real-Time Systems and Their Programming Languages 4:e upplagan

Articles

Compendia

Code Name Scope Grading scale
LAB1 Laboratory work 2 credits U, G
TEN1 Written examination 4 credits U, 3, 4, 5
Lab assignments lead to a written report within the group. Credit is given after a verbal examination of, and demonstration by, individual group members.

Books

Burns & Wellings, (2009) Real-Time Systems and Their Programming Languages 4:e upplagan

Articles

Compendia

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize
I U A Modules Comment
1. DISCIPLINARY KNOWLEDGE AND REASONING
1.1 Knowledge of underlying mathematics and science (G1X level)

                            
1.2 Fundamental engineering knowledge (G1X level)
X
LAB1
TEN1

                            
1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
X
X
LAB1
TEN1

                            
1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)

                            
1.5 Insight into current research and development work

                            
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
2.1 Analytical reasoning and problem solving
X
X
LAB1

                            
2.2 Experimentation, investigation, and knowledge discovery
X
X
LAB1

                            
2.3 System thinking
X
X
LAB1

                            
2.4 Attitudes, thought, and learning
X
X
LAB1
TEN1

                            
2.5 Ethics, equity, and other responsibilities
X

                            
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
3.1 Teamwork
X

                            
3.2 Communications
X
X
LAB1
TEN1

                            
3.3 Communication in foreign languages
X

                            
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
4.1 External, societal, and environmental context

                            
4.2 Enterprise and business context
X

                            
4.3 Conceiving, system engineering and management
X
X
LAB1
TEN1

                            
4.4 Designing
X
X
LAB1
TEN1

                            
4.5 Implementing

                            
4.6 Operating
X

                            
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development

                            
5.2 Economic conditions for knowledge development

                            
5.3 Identification of needs, structuring and planning of research or development projects

                            
5.4 Execution of research or development projects

                            
5.5 Presentation and evaluation of research or development projects

                            

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