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Sporadic Server Scheduling in Linux Theory vs. Practice Mark Stanovich Theodore Baker Andy Wang

Sporadic Server Scheduling in Linux Theory vs. Practice Mark Stanovich Theodore Baker Andy Wang. Real-Time Scheduling Theory. Analysis techniques to design a system to meet timing constraints Schedulability analysis Workload models Processor models Scheduling algorithms.

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Sporadic Server Scheduling in Linux Theory vs. Practice Mark Stanovich Theodore Baker Andy Wang

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  1. Sporadic Server Scheduling in Linux Theory vs. Practice Mark Stanovich Theodore Baker Andy Wang

  2. Real-Time Scheduling Theory • Analysis techniques to design a system to meet timing constraints • Schedulabilityanalysis • Workload models • Processor models • Scheduling algorithms

  3. Real-Time Scheduling Theory • Analysis techniques to design a system to meet timing constraints • Schedulabilityanalysis • Workload models • Processor models • Scheduling algorithms

  4. Periodic Task Task = {T, C, D} Task jobs (j1, j2, j3, …) Deadline = D time Computation time WCET = C Period = T Release time 4

  5. Periodic Task sched_setscheduler(SCHED_FIFO) clock_nanosleep()

  6. Periodic Task • Assumptions • WCET is reliable • Arrivals are periodic • Not realistic for most tasks

  7. Polling Server Replenishment period time Job arrivals Initial budget time

  8. Polling Server • Type of aperiodic server • CPU time no worse than an equivalent periodic task • Can be modeled as a periodic task • WCET = Initial Budget • Period = Replenishment Period • Budget consumed as CPU time is used • CPU time forfeited if not used • Replenish budget every period

  9. Polling Server • Good • Bounds CPU time • Analyzable workload • Simplicity • Can be better • Faster response time if budget is not forfeited

  10. Sporadic Server Replenishment period time Job arrivals Initial budget time replenishments

  11. Sporadic Server • Originally proposed by Sprunt et. al. • Parameters • Initial budget • Replenishment period • Bounds CPU interference for other tasks • Fits into the periodic task workload model • Better avg. response time than polling server

  12. Sporadic Server • Scheduling algorithm for fixed-task-priority systems • Can be used in UNIX priority model • SCHED_SPORADIC is a version of SS defined in POSIX definition

  13. Implementation • Linux 2.6.38 • Softirq threading patch ported from earlier RT patch • Sporadic server implementation • Uniprocessor

  14. Sporadic Server Performance • Metrics • Interference for lower priority tasks • Average response time

  15. An experiment B A Sends UDP packet with current timestamp Receives UDP packets Calculate response time based on arrival at UDP layer Measure CPU time for 10 second burst

  16. Measuring CPU Time • Regher's “hourglass” technique • Constantly read time stamp counter • Detect preemptions by larger gaps • Sum execution chunks • Hourglass thread lower than SS thread • Measures interference from SS thread

  17. Measuring CPU Time • Network receive thread • Sporadic and polling server • Budget = 1 msec • Period = 10 msec • SCHED_FIFO • Hourglass thread • SCHED_FIFO • Lower priority than network receive thread

  18. CPU Utilization

  19. Response Time

  20. Interference • SS budget limited to CPU demand • Additional overheads lower priority tasks • Context switch time • Cache eviction and reloading • Not in theoretical workload model • Guarantees of theory require interference to be included in the analysis

  21. time Polling Server = aperiodic job arrival = aperiodic job CPU time 21

  22. time Sporadic Server = aperiodic job arrival = replenishment period = aperiodic job CPU time 22

  23. Over Provisioning • All context switch time may not be used • e.g., one replenishment per period • Account for CS time on-line • Charge SS for each preemption

  24. CPU Utilization

  25. Response Time

  26. Response Time

  27. Analysis • Light load • Sporadic Server • Low response time • Polling Server • High response time • Heavy load • Sporadic Server • High response time • Dropped packets • Polling Server • Low response time • No dropped packets 27

  28. Can we get the best of both? Sporadic Server Light loads Polling Server Heavy loads 28

  29. Hybrid Server • How to switch • Ensure bounded interference • SS with 1 replenishment is same as polling server • Coalesce replenishments • Push replenishments further into the future • Switching point • Server has work but no budget

  30. time Sporadic Server

  31. time Sporadic Server 31

  32. Response Time

  33. CPU Utilization

  34. Switching • Immediate coalescing may be too extreme • CPU time could be used for better response time • Gradual approach • Coalesce a few replenishments

  35. time Sporadic Server 35

  36. time Sporadic Server 36

  37. time Sporadic Server 37

  38. Response Time

  39. CPU Utilization

  40. Conclusion • Theoretical analysis provides solid guarantees • Implementation must match abstract models • Additional interference terms need to be considered • SS can fit into the theoretical analysis

  41. Deferrable Server

  42. Deferrable Server • Bandwidth Preserving • Allow server to retain budget • Periodically replenish budget • WCET != Budget

  43. Response Time

  44. Replenishment Policy replenishment period replenishment initial budget time arrival time (work available for server) 44

  45. Bandwidth Preservation replenishment period replenishment initial budget time arrival time (work available for server) 45

  46. time Sporadic Server 46

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