Operating Systems CMPSCI 377 Lecture 6: Scheduling

1. Operating SystemsCMPSCI 377Lecture 6: Scheduling Emery Berger University of Massachusetts, Amherst

2. Last Time: Threads & Scheduling • Thread = execution stream within process • User-level, kernel-level, hybrid • There’s no perfect scheduling algorithm! • Competing goals: • Minimize response time • Maximize throughput • Fairness • Policy decision

3. This Time: Scheduling Algorithms • FCFS • First-Come, First-Served • Round-robin • SJF • Multilevel Feedback Queues • Lottery Scheduling

4. Round-Robin Scheduling • Quantum expires: move to back of queue • Variants used in most real systems • Quantum length – • Large: response time increases • quantum )1 = FCFS • Small: throughput decreases • quantum ) 0 = overhead dominates • context switches, cache misses

5. waiting running Example: Round-Robin

6. waiting running Example: Round-Robin

7. waiting running Example: Round-Robin

8. waiting running Example: Round-Robin

9. waiting running Example: Round-Robin

10. waiting running Example: Round-Robin

11. waiting running Example: Round-Robin

12. waiting running Example: Round-Robin

13. waiting running Example: Round-Robin

14. waiting running Example: Round-Robin

15. waiting running Example: Round-Robin • Fair • Long average wait times

16. Round-Robin vs. FCFS • Example 1: • 5 jobs, 100 seconds each, quantum = 1s • ignore context switch time

17. Round-Robin vs. FCFS • Example 1: • 5 jobs, 100 seconds each, quantum = 1s • ignore context switch time

18. Round-Robin vs. FCFS • Example 2: • 5 jobs: 50, 40, 30, 20, 10 seconds each

19. Round-Robin vs. FCFS • Example 2: • 5 jobs: 50, 40, 30, 20, 10 seconds each

20. This Time: Scheduling Algorithms • FCFS • First-Come, First-Served • Round-robin • SJF • Multilevel Feedback Queues • Lottery Scheduling

21. 0 10 30 60 100 150 Example: SJF • Schedule job with least work until I/O or done 10 20 30 40 50

22. 0 10 30 60 100 150 Example: SJF • Schedule job with least work until I/O or done 10 20 30 40 50

23. 0 10 30 60 100 150 Example: SJF • Schedule job with least work until I/O or done 10 20 30 40 50

24. 0 10 30 60 100 150 Example: SJF • Schedule job with least work until I/O or done 10 20 30 40 50

25. 0 10 30 60 100 150 Example: SJF • Schedule job with least work until I/O or done 10 20 30 40 50

26. 0 10 30 60 100 150 Example: SJF • Schedule job with least work until I/O or done 10 20 30 40 50

27. Example: SJF • 5 jobs, length 50, 40, 30, 20, 10 seconds

28. Example: SJF • 5 jobs, length 50, 40, 30, 20, 10 seconds

29. SJF/SRTF: Shortest-Job First • Advantages: • Optimal – minimizes average waiting time • Works for preemptive & non-preemptive schedulers • Preemptive SJF = SRTF • Shortest remaining time first • I/O-bound jobs get priority over CPU-bound jobs • Disadvantages: • Impossible to predict CPU time job has left • Long-running CPU-bound jobs can starve

30. This Time: Scheduling Algorithms • FCFS • First-Come, First-Served • Round-robin • SJF • Multilevel Feedback Queues • Lottery Scheduling

31. Multilevel Feedback Queues (MLFQ) • Use past behavior to predict future! • Overcome prediction problem in SJF • Assumption: • I/O-bound in past, I/O-bound in future • Scheduler favors jobs that use least CPU time • Adaptive: • Change in behavior ) change in scheduling decisions

32. MLFQ: Approximating SJF • Multiple queues, different priorities • Round-robin scheduling at each priority level • Run all at highest priority first, then next, etc. • Can lead to starvation • Increase quantum exponentially at lower priorities

33. MLFQ Example

34. MLFQ: Assigning Priorities • Job starts in highest priority queue • Quantum expires ) CPU-bound • Drop priority one level • Quantum does not expire ) I/O-bound • Increase priority one level • CPU-bound jobs move down,I/O-bound jobs move up

35. Improving Fairness • SJF: optimal, but unfair • Increase fairness = give long jobs CPU time • degrades average waiting time • Solutions: • Each queue – fraction of CPU time • Fair iff even distribution of jobs among queues • Adjust priority of jobs w/o service • Originally done by UNIX • Avoids starvation • Under load, waiting time suffers

36. This Time: Scheduling Algorithms • FCFS • First-Come, First-Served • Round-robin • SJF • Multilevel Feedback Queues • Lottery Scheduling

37. Lottery Scheduling • Every job gets lottery tickets • Each quantum: randomly pick winner • On average:CPU time proportional to # of tickets • Give most tickets to short-running jobs (approximates SJF) • Give every job at least one ticket • Degrades gracefully as load changes

38. Example: Lottery Scheduling • Paying customers: 40%, guests: 60% • 2:1 ticket ratio 2 1 1 1 1 1 1 2

39. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Paying customers: 40%, guests: 60% • 2:1 ticket ratio

40. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Paying customers: 40%, guests: 60% • 2:1 ticket ratio

41. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Paying customers: 40%, guests: 60% • 2:1 ticket ratio

42. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Paying customers: 40%, guests: 60% • 2:1 ticket ratio

43. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Paying customers: 40%, guests: 60% • 2:1 ticket ratio

44. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Paying customers: 40%, guests: 60% • 2:1 ticket ratio

45. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 2/5=40%

46. Example: Lottery Scheduling 2 1 1 1 1 1 1 2 • Probabilistically achieves desired proportions 3/5=60% 2/5=40%

47. Summary of Scheduling Algorithms • FCFS: • unfair, average waiting time poor • Round robin: • fair, average waiting time poor • SJF: • unfair, minimizes average waiting time • requires accurate prediction • Multilevel Feedback Queueing: • approximates SJF • Lottery scheduling: • fair, low average waiting time • poor fit to priority

48. Next Time • Synchronization