Deadline Scheduling for Real-Time Systems

Many real-time systems rely on static scheduling algorithms. This includes cyclic scheduling, rate monotonic scheduling and fixed schedules created by off-line scheduling techniques such as dynamic programming, heuristic search, and simulated annealing. However, for many real-time systems, static scheduling algorithms are quite restrictive and inflexible. For example, highly automated agile manufacturing, command, control and communications, and distributed real-time multimedia applications all operate over long lifetimes and in highly non-deterministic environments. Dynamic real-time scheduling algorithms are more appropriate for these systems and are used in such systems. Many of these algorithms are based on earliest deadline first (EDF) policies. There exists a wealth of literature on EDF-based scheduling with many extensions to deal with sophisticated issues such as precedence constraints, resource requirements, system overload, multi-processors, and distributed systems.
Deadline Scheduling for Real-Time Systems: EDF and Related Algorithms aims at collecting a significant body of knowledge on EDF scheduling for real-time systems, but it does not try to be all-inclusive (the literature is too extensive). The book primarily presents the algorithms and associated analysis, but guidelines, rules, and implementation considerations are also discussed, especially for the more complicated situations where mathematical analysis is difficult.
In general, it is very difficult to codify and taxonomize scheduling knowledge because there are many performance metrics, task characteristics, and system configurations. Also, adding to the complexity is the fact that a variety of algorithms have been designed for different combinations of these considerations. In spite of the recent advances there are still gaps in the solution space and there is a need to integrate the available solutions. For example, a list of issues to consider includes:

• preemptive versus non-preemptive tasks,
• uni-processors versus multi-processors,
• using EDF at dispatch time versus EDF-based planning,
• precedence constraints among tasks,
• resource constraints,
• periodic versus aperiodic versus sporadic tasks,
• scheduling during overload,
• fault tolerance requirements, and

• providing guarantees and levels of guarantees (meeting quality of service requirements).
  Deadline Scheduling for Real-Time Systems: EDF and Related Algorithms should be of interest to researchers, real-time system designers, and instructors and students, either as a focussed course on deadline-based scheduling for real-time systems, or, more likely, as part of a more general course on real-time computing. The book serves as an invaluable reference in this fast-moving field.

  Autorentext
  Giorgio Buttazzo is Full Professor of Computer Engineering at the Scuola Superiore Sant'Anna of Pisa. He graduated in Electronic Engineering at the University of Pisa in 1985, received a Master in Computer Science at the University of Pennsylvania in 1987, and a Ph.D. in Computer Engineering at the Scuola Superiore Sant'Anna of Pisa in 1991. From 1987 to 1988, he worked on active perception and real-time control at the G.R.A.S.P. Laboratory of the University of Pennsylvania, Philadelphia. From 1991 to 1998, he held a position of Assistant Professor at the Scuola Superiore Sant'Anna of Pisa, where he founded and coordinated the RETIS Laboratory on real-time systems. From 1998 to 2005, he held a position of Associate Professor at the University of Pavia, where he directed the robotics laboratory of the Computer Science department. His main research interests include real-time operating systems, dynamic scheduling algorithms, quality of service control, multimedia systems, advanced robotics applications, and neural networks.

  Inhalt
  1 Introduction.- 1.1 Real-Time Systems.- 1.2 Common Misconceptions.- 1.3 A Typical Example of a Real-Time Application.- 1.4 Purpose of this Book.- 1.5 Format of the Book.- References.- 2 Terminology and Assumptions.- 2.1 Task Models, Assumptions and Notation.- 2.2 Static versus Dynamic Scheduling.- 2.3 Metrics.- References.- 3 Fundamentals of EDF Scheduling.- 3.1 Optimality on Uni-Processor Systems.- 3.2 Feasibility Analysis.- 3.3 Summary.- References.- 4 Response Times under EDF Scheduling.- 4.1 Finding Local Maxima.- 4.2 Deadline Busy Periods.- 4.3 Algorithm Description.- 4.4 Extended Task Modeling.- 4.5 Case Study.- 4.6 Summary.- References.- 5 Planning-Based Scheduling.- 5.1 Preliminaries: Load, Metrics, Value Functions.- 5.2 Steps in a Dynamic Planning-Based Scheduling Approach.- 5.3 Algorithms for Dynamic Planning.- 5.4 Timing of the Planning.- 5.5 Implementing Planning-Based Scheduling.- 5.6 Dispatching Jobs in a Planning-based Schedule.- 5.7 Summary.- References.- 6 EDF Scheduling for Shared Resources.- 6.1 The Nature of Resources and the Resulting Scheduling Problems.- 6.2 The Priority Inversion Problem.- 6.3 The Priority Inheritance Protocol.- 6.4 The Dynamic Priority Ceiling Protocol.- 6.5 The Stack Resource Policy.- 6.6 Resource Scheduling in Planning-based Schedulers.- 6.7 Summary.- References.- 7 Precedence Constraints and Shared Resources.- 7.1 Scheduling Dependent Tasks with EDF.- 7.2 The Notion of Quasi-Normality.- 7.3 Integration of Shared Resources and Precedence.- 7.4 Extended Task Model.- 7.5 Summary.- References.- 8 Aperiodic Task Scheduling.- 8.1 Dynamic Priority Exchange server.- 8.2 Dynamic Sporadic Server.- 8.3 Total Bandwidth Server.- 8.4 Earliest Deadline Late server.- 8.5 Improved Priority Exchange server.- 8.6 Performance Results.- 8.7 Summary.- References.- 9 Distributed Scheduling Part I.- 9.1 Distributed Systems An Overview.- 9.2 Holistic Scheduling Based on EDF.- 9.3 Performance.- 9.4 Summary.- References.- 10 Distributed Scheduling Part II.- 10.1 The Spring Complex Task Set Allocation and Scheduling Algorithm.- 10.2 Focussed Addressing and Bidding.- 10.3 Summary.- References.- 11 Summary and Open Questions.- 11.1 Summary.- 11.2 Open Questions.- References.