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Evolving Real-Time Systems using Hierarchical Scheduling and Concurrency Analysis

Evolving Real-Time Systems using Hierarchical Scheduling and Concurrency Analysis. John Regehr Alastair Reid Kirk Webb Michael Parker Jay Lepreau School of Computing, University of Utah. Problem: Evolving real-time and embedded software is hard

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Evolving Real-Time Systems using Hierarchical Scheduling and Concurrency Analysis

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  1. Evolving Real-Time Systemsusing Hierarchical Schedulingand Concurrency Analysis John Regehr Alastair Reid Kirk Webb Michael Parker Jay Lepreau School of Computing, University of Utah

  2. Problem: Evolving real-time and embedded software is hard • Problem: Concurrent software is hard to write and debug • Problem: Traditional task models ignore some important details about real systems

  3. hi FIFO CPU FIFO lo thread A Task Set t1 hi t2 IRQ t3 lo t4 t5 hi t6 t7 t8 lo Key: preemptive non-preemptive

  4. This Talk • Introduces hierarchical execution environments to support analysis of: • Concurrency • Response times • Blocking terms • Dispatch overheads • Results in solving real-time problems on sensor network nodes

  5. Execution Environments • A real-time or embedded system usually supports multiple execution environments • Interrupts • Bottom-half handlers • a.k.a. DPCs, tasklets, deferred handlers • Event handlers • Kernel threads • User threads

  6. An Execution Environment… • Occupies a place in the scheduling hierarchy • Has particular performance characteristics • Has rules: • About actions code running in it may take • About how to synchronize with code in other environments

  7. Related Work • Hierarchical scheduling • Lots of work: Deng et al., Feng & Mok, Lipari et al., Regehr & Stankovic, Saewong et al., Shin & Lee, … • Multiple execution environments • Limited related work here • Concurrency analysis • Lots of work in PL and formal methods communities – but none supporting multiple execution environments

  8. Goal: Evolving Systems • Often desirable to move code between environments • “Promote” code to a higher priority environment • “Demote” code to a lower priority environment • Problem: How do we know when to promote / demote code? • Problem: Very easy to introduce concurrency errors this way • May be lots of code per environment

  9. Example System: Motes • Sensor network nodes • Software based on TinyOS • Very simple “OS” • No threads! • Motes are resource constrained • 4 MHz 8-bit RISC • 4 KB SRAM, 128 KB flash

  10. Problem 1: Long-running tasks cause network errors int1 hi int2 IRQ hi int3 lo CPU calc_crc lo sent FIFO received encrypt Key: preemptive non-preemptive decrypt

  11. Fixed TinyOS 1 int1 hi int2 IRQ hi int3 lo calc_crc CPU sent FIFO1 hi lo received AvrX encrypt lo FIFO2 decrypt Key: preemptive non-preemptive

  12. Results

  13. Problem 2: Missed SPI deadlines cause packet loss timer hi SPI IRQ hi UART lo CPU t1 lo t2 FIFO t3 t4 Key: preemptive non-preemptive

  14. Fixed TinyOS 2 SPI timer hi hi soft_SPI IRQ vIRQ hi lo UART lo CPU t1 lo t2 FIFO t3 t4 Key: preemptive non-preemptive

  15. Results

  16. Problem: How do we know when to promote / demote code? • Solution: Response time analysis • Problem: Very easy to introduce concurrency errors this way • Solution: Concurrency analysis

  17. Real-Time Analysis • Problem: How to analyze response times for hierarchies? • Solution: Map to a problem that we know how to solve • Static priority scheduling • Preemption threshold scheduling • Hierarchies restricted to: • Preemptive priority schedulers • Leaf schedulers can be non-preemptive FIFO or priority

  18. Real-Time Analysis 5 us (0,0) clock hi 2 us (1,1) disk IRQ (2,2) disk_bh hi lo FIFO (2,2) eth_bh CPU lo e1 (4,4) t1 (3,3) event e2 (5,4) thread e3 (6,4) t3 (7,7) Key: preemptive non-preemptive 10 us 2 us

  19. Concurrency Analysis • Problem: How to check for race conditions? • Solution: Task scheduler logic • Static analysis of concurrency across a hierarchy of execution environments

  20. Task Scheduler Logic • Schedulers specify: • Preemption relations among things they schedule • Locks they provide • Axioms propagate effects around the hierarchy • TSL allows us to derive (potential) preemption relations for each pair of tasks in a system • Details in paper…

  21. Concurrency Analysis clock hi disk IRQ disk_bh hi lo FIFO eth_bh CPU lo e1 t1 event e2 thread e3 t3 Key: preemptive non-preemptive

  22. Contributions • New notation for describing structure of systems software • Heuristics for evolving systems • Algorithms for hierarchical priority and FIFO schedulers: • Whole-program concurrency analysis • Response time analysis • Experimental validation

  23. Evolving Real-Time Systemsusing Hierarchical Schedulingand Concurrency Analysis John Regehr Alastair Reid Kirk Webb Michael Parker Jay Lepreau School of Computing, University of Utah

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