1. Processes and operating systems
Scheduling policies:
RMS;
EDF.
Scheduling modeling assumptions.
Interprocess communication.
Power management.
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2. Overheads for Computers as Components
Metrics
How do we evaluate a scheduling policy:
Ability to satisfy all deadlines.
CPU utilization---percentage of time devoted to useful work.
Scheduling overhead---time required to make scheduling decision.
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3. Rate monotonic scheduling
RMS (Liu and Layland): widely-used, analyzable scheduling policy.
Analysis is known as Rate Monotonic Analysis (RMA).
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4. Overheads for Computers as Components
RMA model
All process run on single CPU.
Zero context switch time.
No data dependencies between processes.
Process execution time is constant.
Deadline is at end of period.
Highest-priority ready process runs.
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5. Overheads for Computers as Components
Process parameters
Ti is computation time of process i; ti is period of process i.
period ti Pi
computation time Ti
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6. Rate-monotonic analysis
Response time: time required to finish process.
Critical instant: scheduling state that gives worst response time.
Critical instant occurs when all higher-priority processes are ready to execute.
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7. Overheads for Computers as Components
Critical instant P1 P2 P3
interfering processes P1 P2 P3
critical
instant P4
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8. Overheads for Computers as Components
RMS priorities
Optimal (fixed) priority assignment:
shortest-period process gets highest priority;
priority inversely proportional to period;
break ties arbitrarily.
No fixed-priority scheme does better.
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9. Overheads for Computers as Components
RMS example
P2 period P2
P1 period P1 P1 P1 5 10
time
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10. Overheads for Computers as Components
RMS CPU utilization
Utilization for n processes is
S i Ti / ti
As number of tasks approaches infinity, maximum utilization approaches 69%.
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11. RMS CPU utilization, cont’d.
RMS cannot asymptotically guarantee use 100% of CPU, even with zero context switch overhead.
Must keep idle cycles available to handle worst-case scenario.
However, RMS guarantees all processes will always meet their deadlines.
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Overheads for Computers as Components

12. Overheads for Computers as Components
RMS implementation
Efficient implementation:
scan processes;
choose highest-priority active process.
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13. Earliest-deadline-first scheduling
EDF: dynamic priority scheduling scheme.
Process closest to its deadline has highest priority.
Requires recalculating processes at every timer interrupt.
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14. Overheads for Computers as Components
EDF example P1 P2
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15. Overheads for Computers as Components
EDF analysis
EDF can use 100% of CPU.
But EDF may miss a deadline.
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16. Overheads for Computers as Components
EDF implementation
On each timer interrupt:
compute time to deadline;
choose process closest to deadline.
Generally considered too expensive to use in practice.
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17. Fixing scheduling problems
What if your set of processes is unschedulable?
Change deadlines in requirements.
Reduce execution times of processes.
Get a faster CPU.
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18. Overheads for Computers as Components
Priority inversion
Priority inversion: low-priority process keeps high-priority process from running.
Improper use of system resources can cause scheduling problems:
Low-priority process grabs I/O device.
High-priority device needs I/O device, but can’t get it until low-priority process is done.
Can cause deadlock.
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19. Solving priority inversion
Give priorities to system resources.
Have process inherit the priority of a resource that it requests.
Low-priority process inherits priority of device if higher.
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20. Overheads for Computers as Components
Data dependencies
Data dependencies allow us to improve utilization.
Restrict combination of processes that can run simultaneously.
P1 and P2 can’t run simultaneously. P1 P2
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21. Context-switching time
Non-zero context switch time can push limits of a tight schedule.
Hard to calculate effects---depends on order of context switches.
In practice, OS context switch overhead is small.
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22. Overheads for Computers as Components
What about interrupts?
Interrupts take time away from processes.
Perform minimum work possible in the interrupt handler. P1 OS P2
intr OS P3
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23. Device processing structure
Interrupt service routine (ISR) performs minimal I/O.
Get register values, put register values.
Interrupt service process/thread performs most of device function.
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24. POSIX scheduling policies
SCHED_FIFO: RMS
SCHED_RR: round-robin
within a priority level, processes are time-sliced in round-robin fashion
SCHED_OTHER: undefined scheduling policy used to mix non-real-time and real-time processes.
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25. Interprocess communication
OS provides interprocess communication mechanisms:
various efficiencies;
communication power.
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26. Overheads for Computers as Components
Signals
A Unix mechanism for simple communication between processes.
Analogous to an interrupt---forces execution of a process at a given location.
But a signal is caused by one process with a function call.
No data---can only pass type of signal.
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27. Overheads for Computers as Components
POSIX signals
Must declare a signal handler for the process using sigaction().
Handler is called when signal is received.
A signal can be sent with sigqueue():
sigqueue(destpid,SIGRTMAX-1,sval)
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28. Overheads for Computers as Components
POSIX signal types
SIGABRT: abort
SIGTERM: terminate process
SIGFPE: floating point exception
SIGILL: illegal instruction
SIGKILL: unavoidable process termination
SIGUSR1, SIGUSR2: user defined
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29. Overheads for Computers as Components
Signals in UML
More general than Unix signal---may carry arbitrary data:
someClass
<<signal>>
aSig
<<send>>
sigbehavior()
p : integer
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30. Overheads for Computers as Components
POSIX shared memory
POSIX supports counting semaphores with _POSIX_SEMAPHORES option.
Semaphore with N resources will not block until N processes hold the semaphore.
Semaphores are given name:
/sem1
P() is sem_wait(), V() is sem_post().
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31. POSIX message-based communication
Unix pipe supports messages between processes.
Parent process uses pipe() to create a pipe.
Pipe is created before child is created so that pipe ID can be passed to child.
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32. Overheads for Computers as Components
POSIX pipe example
/* create the pipe */
if (pipe(pipe_ends) < 0) { perror(“pipe”); break; }
/* create the process */
childid = fork();
if (childid == 0) { /* child reads from pipe_ends[1] */
childargs[0] = pipe_ends[1];
execv(“mychild”,childargs);
perror(“execv”);
exit(1); }
else { /* parent writes to pipe_ends[0] */ … }
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33. Evaluating performance
May want to test:
context switch time assumptions;
scheduling policy.
Can use OS simulator to exercise process set, trace system behavior.
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34. Overheads for Computers as Components
Processes and caches
Processes can cause additional caching problems.
Even if individual processes are well-behaved, processes may interfere with each other.
Worst-case execution time with bad behavior is usually much worse than execution time with good cache behavior.
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35. Overheads for Computers as Components
Power optimization
Power management: determining how system resources are scheduled/used to control power consumption.
OS can manage for power just as it manages for time.
OS reduces power by shutting down units.
May have partial shutdown modes.
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36. Power management and performance
Power management and performance are often at odds.
Entering power-down mode consumes
energy,
time.
Leaving power-down mode consumes
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37. Simple power management policies
Request-driven: power up once request is received. Adds delay to response.
Predictive shutdown: try to predict how long you have before next request.
May start up in advance of request in anticipation of a new request.
If you predict wrong, you will incur additional delay while starting up.
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38. Probabilistic shutdown
Assume service requests are probabilistic.
Optimize expected values:
power consumption;
response time.
Simple probabilistic: shut down after time Ton, turn back on after waiting for Toff.
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39. Advanced Configuration and Power Interface
ACPI: open standard for power management services.
applications
device
drivers
OS kernel
power
management
ACPI BIOS
Hardware platform
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40. ACPI global power states
G3: mechanical off
G2: soft off
S1: low wake-up latency with no loss of context
S2: low latency with loss of CPU/cache state
S3: low latency with loss of all state except memory
S4: lowest-power state with all devices off
G1: sleeping state
G0: working state
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Overheads for Computers as Components