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Real-Time Scheduling

Real-Time Scheduling. CS 3204 – Operating Systems Lecture 13 10/3/2006 Shahrooz Feizabadi. Real-Time Systems. Systems that must service requests within a precise time constraint:. Air traffic control systems Railway switching systems Industrial automation Robotics Military.

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Real-Time Scheduling

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  1. Real-Time Scheduling CS 3204 – Operating Systems Lecture 13 10/3/2006 Shahrooz Feizabadi

  2. Real-Time Systems Systems that must service requests within a precise time constraint: • Air traffic control systems • Railway switching systems • Industrial automation • Robotics • Military Generally, systems that must respond to external physical phenomena.

  3. Tracking System Example • Dynamic trajectory calculations • False alarms • Verification • System response • Real-time clock • 687m error!

  4. System Resources Different approaches to resource management: • General-purpose OS • Extensible time horizon: all tasks eventually finish • Similarly, elastic memory: demand paging • Fairness • Non-starvation • Real-Time system • Fixed resources • Tasks adjusted accordingly • Predictability

  5. Schedulers • Preemptive / non-preemptive • Static / dynamic • On-line / off-line • Optimal / heuristic • Clairvoyance

  6. Ci t ai si fi di Real-Time Task Parameters Computation time Arrival time start time finish time deadline

  7. Real-Time Tasks Ci Laxity (slack) t ai si fi di Ci Deadline miss x t ai si di fi

  8. RMA • Rate Monotonic Algorithm • Static • Preemptive • Fixed-priority assignment • Periodic tasks • Guarantee-based • Hard real-time correctness – all deadlines always met

  9. RMA (continued) RMA: Assign unique priorities, in descending order, to tasks ordered by ascending periods: the shorter the period, the higher the priority.

  10. RMA – Example Assume deadline equals period (T). A 0 5 10 15 20 25

  11. RMA – Example A B 0 5 10 15 20 25

  12. RMA – Example A B C 0 5 10 15 20 25

  13. RMA – Example A B C 0 5 10 15 20 25

  14. RMA – Example A B C 0 5 10 15 20 25

  15. RMA – Example A B C 0 5 10 15 20 25

  16. RMA – Example A B C 0 5 10 15 20 25

  17. RMA – Example A preempts C A B C 0 5 10 15 20 25

  18. RMA – Example A B C 0 5 10 15 20 25

  19. RMA – Example A B C 0 5 10 15 20 25

  20. RMA – Example A preempts B A B C 0 5 10 15 20 25

  21. RMA – Example C arrives A B C 0 5 10 15 20 25

  22. RMA – Example A B C 0 5 10 15 20 25

  23. RMA – Example A B C 0 5 10 15 20 25

  24. RMA – Example A B C 0 5 10 15 20 25

  25. RMA (continued) • How far can we push this? • Constraints • Number of tasks? • Periods? • Computational times?

  26. Processor Utilization Factor Fraction of CPU time spent in execution of tasks: Otherwise stated: sum of the individual relative load contribution of each task in the task-set. Provides an indication of system-wide computational load.

  27. Feasibility Test RMA guarantee: No deadlines will be missed under rate monotonic scheduling if the following condition holds:

  28. Feasibility Test (continued) • Note that: • That is, any task-set with a CPU utilization factor of 69% or less is schedulable under RMA • Sufficient, but not necessary condition

  29. Optimality RMA is an optimal fixed-priority assignment algorithm: no other fixed-priority algorithms can schedule a task set that cannot be scheduled under RMA.

  30. EDF • Earliest Deadline First • Earlier the deadline, higher the priority. • Dynamic assignment • On-line • No periodicity assumptions – can schedule aperiodic tasks.

  31. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25 Hyper-period

  32. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25

  33. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25

  34. EDF – Example Assume deadline equals period (T). Lexical order tie breaker A B C 0 5 10 15 20 25

  35. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25

  36. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25

  37. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25

  38. EDF – Example Assume deadline equals period (T). A B C 0 5 10 15 20 25 Pattern repeats

  39. EDF Properties • Feasibility test: • U = 100% in example • Bound theoretical • Sufficient and necessary • Optimal

  40. Overload • Hard real-time • No deadlines misses. • Dimension system to meet exact timing requirements. • Soft real-time • May encounter transient or sustained overload. • Design algorithm to achieve desired temporal behavior.

  41. Real-Time Overload Scheduling • Runtime uncertainty • Dynamic system • Aggregate demand exceeds capacity • Fixed available bandwidth • Must shed load • Starvation • Who survives?

  42. EDF Domino Effect Deadline sole scheduling parameter

  43. EDF Domino Effect Cascading deadline misses X X X Deadline sole scheduling parameter

  44. Load Shedding • Feasible schedule if any task excluded in example? • Selection criteria • Fitness metric • Second dimension: utility

  45. Load Shedding Overload detected X X X

  46. Load Shedding Two scheduling parameters: deadline and utility u = 3 Least valuable task u = 1 X u = 5 X u = 7 X

  47. Load Shedding u = 3 Least valuable task u = 1 X u = 5 u = 7

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