Techniques for Enhancing the Temporal Predictability of Real-time Embedded Systems Employing a Time-triggered Software Architecture PDF Download
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Author: Adi Abdelhalim Maaita
Publisher:
ISBN:
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Languages : en
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Author: Adi Abdelhalim Maaita
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Michael J. Pont
Publisher: Lulu.com
ISBN: 0993035507
Category : Computers
Languages : en
Pages : 399
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This is the first edition of 'The Engineering of Reliable Embedded Systems': it is released here largely for historical reasons. (Please consider purchasing 'ERES2' instead.) [The second edition will be available for purchase here from June 2017.]
Author: Hermann Kopetz
Publisher: Springer Science & Business Media
ISBN: 0306470551
Category : Computers
Languages : en
Pages : 347
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7. 6 Performance Comparison: ET versus TT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 7. 7 The Physical Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 Points to Remember . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 Bibliographic Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Review Questions and Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Chapter 8: The Time-Triggered Protocols. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 8. 1 Introduction to Time-Triggered Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 8. 2 Overview of the TTP/C Protocol Layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 8. 3 TheBasic CNI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 Internal Operation of TTP/C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 8. 4 8. 5 TTP/A for Field Bus Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Points to Remember. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Bibliographic Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Review Questions and Problems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Chapter 9: Input/Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 9. 1 The Dual Role of Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 9. 2 Agreement Protocol. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 9. 3 Sampling and Polling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 9. 4 Interrupts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 9. 5 Sensors and Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 9. 6 Physical Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Points to Remember. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208 Bibliographic Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Review Questions and Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Chapter 10: Real-Time Operating Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 10. 1 Task Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 10. 2 Interprocess Communication. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 10. 3 Time Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 10. 4 Error Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 10. 5 A Case Study: ERCOS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Points to Remember. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Bibliographic Notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 Review Questions and Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 Chapter 11: Real-Time Scheduling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 11. 1 The Scheduling Problem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 11. 2 The Adversary Argument. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 11. 3 Dynamic Scheduling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 x TABLE OF CONTENTS 11. 4 Static Scheduling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Points to Remember. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 Bibliographic Notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 Review Questions and Problems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 Chapter 12: Validation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 12. 1 Building aConvincing Safety Case. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246 12. 2 Formal Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 12. 3 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Author: Ayman Khalifa Ghaly Gendy
Publisher:
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Languages : en
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It is often argued that time-triggered (TT) architectures are the most suitable basis for safety-related applications as their use tends to result in highly-predictable system behaviour. This predictability is increased when TT architectures are coupled with the use of co-operative (or "non pre-emptive") task sets. Despite many attractive properties, such "time-triggered co-operative" (TTC) and related "time-triggered hybrid" (TTH) architectures rarely receive much attention in the research literature. One important reason for this is that these designs are seen to be "fragile": that is, small changes to the task set may require revisions to the whole schedule. Such revisions are seen as challenging and time consuming. To tackle this problem two novel algorithms (TTSA1 and TTSA2), which help to automate the process of scheduler selection and configuration, are introduced. While searching for a workable schedule, both the algorithms try to ensure that all task constraints are met, a co-operative scheduler is used whenever possible and the power consumption is kept as low as possible. The effectiveness of these algorithms is tested by means of empirical trials. Both TTSA1 and TTSA2, like most of scheduling algorithms introduced in the literature, rely on knowledge of task worst-case execution time (WCET). Unfortunately, determining the WCET of tasks is rarely straightforward. Even in situations where accurate WCET estimates are available at design time, variations in task execution time, between its best-case execution time (BCET) and its WCET, may still affect the system predictability and/or violate task constraints. In an effort to address this problem, a set of code-balancing techniques is introduced. Using an empirical study it is demonstrated that these techniques help in reducing the variations in task execution time, and hence increase the system predictability. These goals are achieved with a reduced power-consumption overhead, compared to alternative solutions.
Author: Mouaaz Nahas
Publisher:
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Category :
Languages : en
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Author: M.G. Rodd
Publisher: Elsevier
ISBN: 0080983960
Category : Computers
Languages : en
Pages : 227
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The authors set out to address fundamental design issues facing engineers when developing the software for real-time computer-based control systems – in which all programs must be safe, reliable, predictable and able to cope with the occurence of faults. Despite rapid progress in computer technology, the attention of designers is still focused on finding logically correct algorithms to implement the required control. It has, however, become evident that this is insufficient and that attention must be paid to meeting the complex timing interactions which occur between the systems under control and the computers controlling them. This book suggests that the answers lie in the use of understandable, engineering-relevant, mathematically sound tools for expressing and analysing the complex temporal interactions. Timing Analysis of Real-Time Software is not a designer's handbook; rather it discusses the nature of the problems involved and how they can be handled. The focus is on the use of modelling techniques based on the so-called Quirk-model, initially developed in the United Kingdom and, over the past decade, extensively developed in institutions in the ex-Soviet Union and Europe. This book shows how the techniques can be used to form the basis of a new generation of CASE (computer assisted software engineering) tools, and examples are given of how these can be used to design embedded systems ranging from digital controllers through to communication protocol handlers.
Author: Phillip A. Laplante
Publisher: Wiley-IEEE Press
ISBN:
Category : Computers
Languages : en
Pages : 392
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"IEEE Press is pleased to bring you this Second Edition of Phillip A. Laplante's best-selling and widely-acclaimed practical guide to building real-time systems. This book is essential for improved system designs, faster computation, better insights, and ultimate cost savings. Unlike any other book in the field, REAL-TIME SYSTEMS DESIGN AND ANALYSIS provides a holistic, systems-based approach that is devised to help engineers write problem-solving software. Laplante's no-nonsense guide to real-time system design features practical coverage of: Related technologies and their histories Time-saving tips * Hands-on instructions Pascal code Insights into decreasing ramp-up times and more!"
Author:
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Category : Integrated circuits
Languages : en
Pages : 492
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Author: Teera Phatrapornnant
Publisher:
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Category :
Languages : en
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Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
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Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
