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Real Time Systems, 6 credits
Realtidssystem, 6 hp
TDDD07
Main field of study
Computer Science and Engineering Computer ScienceCourse level
Second cycleCourse type
Programme courseExaminer
Simin Nadjm-TehraniDirector of studies or equivalent
Ola LeiflerEducation components
Preliminary scheduled hours: 50 hRecommended self-study hours: 110 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Computer Science and Engineering, Computer ScienceCourse level
Second cycleAdvancement level
A1XCourse offered for
- Master's Programme in Computer Science
- Master's Programme in Electronics Engineering
- 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
| 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.
Grades
Four-grade scale, LiU, U, 3, 4, 5Course literature
Articles and e-book chapters recommended on the course web pages.
Department
Institutionen för datavetenskapDirector of Studies or equivalent
Ola LeiflerExaminer
Simin Nadjm-TehraniCourse website and other links
http://www.ida.liu.se/~TDDD07Education components
Preliminary scheduled hours: 50 hRecommended 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) |
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| 1.2 Fundamental engineering knowledge (G1X level) |
|
X
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LAB1
TEN1
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
X
|
X
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LAB1
TEN1
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
|
X
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X
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LAB1
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| 2.2 Experimentation, investigation, and knowledge discovery |
|
X
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X
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LAB1
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| 2.3 System thinking |
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X
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X
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LAB1
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| 2.4 Attitudes, thought, and learning |
|
X
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X
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LAB1
TEN1
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| 2.5 Ethics, equity, and other responsibilities |
X
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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| 3.2 Communications |
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X
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X
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LAB1
TEN1
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| 3.3 Communication in foreign languages |
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X
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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X
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| 4.3 Conceiving, system engineering and management |
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X
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X
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LAB1
TEN1
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| 4.4 Designing |
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X
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X
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LAB1
TEN1
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| 4.5 Implementing |
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| 4.6 Operating |
X
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| 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 |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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