ECE 697: Real-Time Systems

1. ECE 697: Real-Time Systems • Instructor: C. M. Krishna • krishna@ecs.umass.edu; (413) 545-0766 • Office Hours (on-campus): Tues: 4:00--4:45 PM • Off-campus Contact: By e-mail and telephone • Course Grading: • Three in-term tests: 18% each • Final exam (cumulative): 26% • Homework/simulation exercises: 20% • Homework is to be done individually

2. Coverage • Introduction to real-time systems • Performance measures • Task allocation and scheduling techniques • Power and energy issues • Communication algorithms • Fault tolerance and reliability evaluation • Clock synchronization

3. Textbook • C. M. Krishna and K. G. Shin, Real-Time Systems, McGraw-Hill, 1997. • On-campus students: I’ve put a copy on reserve in the Physical Sciences Library; I’ll make another copy available in the Architecture & Real-Time Lab • Off-campus students: Check your nearest technical library • Also available from bookstores (online and traditional) • See the course web page for a pointer to the typo list: http://www-unix.ecs.umass.edu/~krishna/rtcourse.html

4. Course Notes • A few PowerPoint slides: Will be posted on the course website • Mostly handwritten in class: The more important bits will be scanned and available through the course website after the lecture • Readings beyond the text will be used for • Real-time communication protocols • Energy- and power-aware computing

5. Today’s Topics • What is a real-time system? • General characteristics • Hard and soft real-time systems • Performance Measures • Why are they important? • For general-purpose systems • For real-time systems • Uniprocessor task scheduling

6. What is a Real-Time System? • Any system in which a deadline plays a central role in its perceived performance • But timely response is important for general-purpose systems, too! • There is no hard-and-fast demarcation between a real-time system and a general-purpose system • Systems in the control loop are always real-time

7. Types of RTS • Hard Real-Time Systems • Missing a deadline (or series of deadlines) can cause a significant loss to the application. • Examples: Fly-by-wire, power-plant, and grid control • Soft Real-Time Systems • Missing a deadline causes the quality of service to degrade, but nothing terrible happens • Examples: Video-on-demand, teleconferencing

8. Example: Fly-by-wire • Used initially in military aircraft • Dynamics time-constants are too small for humans to be effective controllers • Philosophy: • Pilot sets policy • Computer carries out low-level actions to implement that policy • If too many deadlines are missed in a row, the aircraft can crash

9. Feedback Loop (From C. M. Krishna & K. G. Shin: NASA Con. Report 3807, 1984)

10. Impact of Feedback Delay (Simulation Example) Elevator Deflections During Landing

11. Performance Measures • Traditional Measures • Throughput: Average number of instructions processed per second • Availability: Fraction of time for which the system is up • Reliability: Probability that the system will remain up throughout a designated interval

12. Special-Purpose Measure • Performability • Published by John Meyer in 1980 • Identify accomplishment levels, {A0, A1, A2, …, An}, for the application • Determine the probability, P(Ai), that the real-time system will be able to perform in such a way that Ai will be accomplished • Performability is the vector (P(A0), P(A1), …, P(An)) • Application-focused measure

13. Task Allocation and Scheduling • How to assign tasks to processors and to schedule them in such a way that deadlines are met • Our initial focus: uniprocessor task scheduling

14. Uniprocessor Task Scheduling • Initial Assumptions: • Each task is periodic • Periods of different tasks may be different • Worst-case task execution times are known • Relative deadline of a task is equal to its period • No dependencies between tasks: they are independent • Only resource constraint considered is execution time • No critical sections • Preemption costs are negligible • Tasks must be completed for output to have any value

15. Standard Scheduling Algorithms • Rate-Monotonic (RM) Algorithm: • Static priority • Higher-frequency tasks have higher priority • Earliest-Deadline First (EDF) Algorithm: • Dynamic priority • Task with the earliest absolute deadline has highest priority

16. RMA • Task priority is inversely proportional to the task period (directly proportional to task frequency) • At any moment, the processor is either • idle if there are no tasks to run, or • running the highest-priority task available • A lower-priority task can suffer many preemptions • To a task, lower-priority tasks are effectively invisible

17. RMA • Example • Schedulability criteria: • Sufficiency condition (Liu & Layland, 1973) • Necessary & sufficient conditions (Joseph & Pandya, 1986; Lehoczky, Sha, Ding 1989)

18. RMA • Critical Instant of a Task: An instant at which a request for that task will have the largest response time • Critical Time-zone of a Task: Interval between a critical instant of that task and the completion time of that task • Critical Instant Theorem: Critical instant of a task T_i occurs whenever T_i arrives simultaneously with all higher-priority tasks

19. RMA: Scheulability Check • The Critical Instant Theorem leads to a schedulability check: • If a task is released at the same time as all of the tasks of higher priority and it meets its deadline, then it will meet its deadline under all circumstances

20. RMA: Schedulability Test • If a task is released simultaneously with all higher-priority tasks, determine when it will be done • If this completion time is no later than this task’s deadline, we have succeeded with this task • Find a systematic procedure to turn this process into a necessary-and-sufficient schedulability check

21. RMA: Schedulability • Start with a single-task set and obtain its schedulability conditions • Extend this to a two-task set • Exploit any intuition gained to generalize this