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SubjectAttempted summary of suspend-blockers LKML thread, take three
Final report from this particular angel-free zone for the time being...

This is the third and final version of my Android requirements list
(last version available at http://lkml.org/lkml/2010/8/4/409). Again,
this email is an attempt to present the Android guys' requirements, based
on my interpretation of LKML discussions. This past week's discussion
was quite productive, and I thank everyone who took part.

Please note that I am not proposing a solution that meets these
requirements, nor am I attempting to judge the various proposed solutions.
In fact, I am not even trying to judge whether the requirements are
optimal, or even whether or not they make sense at all. My only goal at
the moment is to improve our collective understanding of what the Android
folks' requirements are. That said, I do discuss example mechanisms
where needed to clarify the meaning of the requirements. This should
not be interpreted as a preference for any given example mechanism.

Thanx, Paul

------------------------------------------------------------------------
CONTENTS

o DEFINITIONS
o CATEGORIES OF APPLICATION BEHAVIOR
o REQUIREMENTS
o NICE-TO-HAVES
o APPARENT NON-REQUIREMENTS
o SUGGESTED USAGE
o POWER-OPTIMIZED APPLICATIONS
o OTHER EXAMPLE APPLICATIONS
o ACKNOWLEDGMENTS


DEFINITIONS

These have been updated based on LKML and linux-pm discussions. The names
are probably still sub-optimal, but incremental progress is nevertheless
a very good thing.

o "Ill-behaved application" AKA "untrusted application" AKA
"crappy application". The Android guys seem to be thinking in
terms of applications that are well-designed and well-implemented
in general, but which do not take power consumption or battery
life into account. Examples include applications designed for
externally powered PCs. Many other people seemed to instead be
thinking in terms of an ill-conceived or useless application,
perhaps exemplified by "bouncing cows".

This document uses "power-oblivious applications" to mean
applications that are well-designed and well-implemented in in
general, but which do not take power consumption or battery life
into account.

o "PM-driving application" are applications that are permitted
to acquire suspend blockers on Android. Verion 8 of the
suspend-blocker patch seems to use group permissions to determine
which processes are classified as power aware. Android uses a
user-level daemon to classify app-store apps as PM-driving or not.
More generally, PM-driving applications are those that have
permission to exert some control over the system's sleep state.

Note that an application might be power-oblivious on one
Android device and PM-driving on another, depending on whether
the user allows that application to acquire suspend blockers.
The classification might even change over time. For example,
a user might give an application PM-driving status initially,
but change his or her mind after some experience with that
application.

o Oddly enough, "power-optimized applications" were not discussed.
See "POWER-OPTIMIZED APPLICATIONS" below for a brief introduction.
The short version is that power-optimized applications are those
PM-driving applications that have been aggressively tuned to
reduce power consumption.

o Individual devices in an embedded system can enter "device
low-power states" when not in use.

o The system as a whole can enter a "system sleep state" when
the system as a whole is not in use. Suspend blockers are about
system sleep states rather than device low-power states.

o There was much discussion of "idle" (AKA "deep idle") and
"suspend" (as in current Linux-kernel suspend operations).
The following characteristics distinguish "idle" from "suspend":

1. Idle states are entered by a given CPU only there are no
runnable tasks for that CPU. In contrast, opportunistic
suspend can halt the entire system even when there
are tasks that are ready, willing, and able to run.
(But please note that this might not apply to real-time
tasks.)

Freezing of subsets of applications is somewhat related
to the idle/suspend discussion, but is covered in a
later section of this document.

2. There can be a set of input events that do not bring
the system out of suspend, but which would bring the
system out of idle. Exactly which events are in this
set depends both on hardware capabilities and on the
platform/application policy. For example, on one of
the Android-based smartphones, touchscreen input is
ignored when the system is suspended, but is handled
when idle.

3. The system comes out of idle when a timer expires. In
contrast, timers might or might not bring the system
out of suspend, depending on both hardware capabilities
and platform/application policy.


CATEGORIES OF APPLICATION BEHAVIOR

There are a number of categories of application behavior with respect
to power management and energy efficiency. These can be classified via
the following questions: (1) What degree of control is an application
permitted over its own behavior? (2) What degree of control is an
application permitted over the power state of individual devices within
the system? (3) What degree of control is an application permitted
over the system sleep state? (4) To what degree has the application
been tuned to reduce its power consumption, either in isolation or in
conjunction with other applications that might be running concurrently?

These categories are discussed below.

o What degree of control is an application permitted over its
own behavior?

The Linux kernel already has many controls over application
behavior:

o the CAP_ capabilities from include/linux/capability.h.

o Processes can be assigned to multiple groups, allowing
them privileged access to portions of the filesystem.

o The chroot() system call limits a process's access to the
specified subtree of the filesystem.

o The ulimit facility can limit CPU consumption, number
of processes, memory, etc. on a per-user basis. The
rlimit facility has similar effects on a per-process
basis.

o The mlockall() system call provides privileged access
to memory, avoiding page-fault overhead.

But more relevant to this discussion, real-time processes are
permitted a much higher degree of control over the timing of their
execution than are non-real-time processes. However, suspending
the system destroys any pretense of offering real-time guarantees,
which might explain much of the annoyance towards suspend blockers
from the real-time and scheduler folks. For but one example,
Peter Zijlstra suggested that he would merge a patch that acquired
a suspend blocker any time that the runqueues were non-empty.
My first reaction was amusement at this vintage Peter Zijlstra
response, and my second reaction was that it was a futile gesture,
as the Android guys would simply back out any such change.

After more thought, however, a variation of Peter's approach
might well be the key to resolving this tension between
real-time response on the one hand and Android's desire to
conserve power at any cost on the other. Given that suspending
destroys real-time response, why not acquire a suspend blocker
any time there is a user-created real-time task in the system,
whether runnable or not? Of course, a simpler approach would
be to make Android's OPPORTUNISTIC_SUSPEND depend on !PREEMPT_RT.

o What degree of control is an application permitted over the power
state of individual devices within the system?

Is the application in question permitted to power down the
CPU or peripheral devices? As more of the power control is
automated based on usage, it is possible that this question will
become less relevant. The longer the latency and the greater
the energy consumption of a power-up/power-down sequence for
a given device, the less suitable that device is for automatic
power-up/power-down decisions. Cache SRAMs and main-memory
DRAM tend to be less suitable for automation for this reason.

o What degree of control is an application permitted over the
system sleep state?

Is the application permitted to suspend the device? Or in the
case of Android, is the application permitted to acquire a
suspend blocker, which prevents the device from being suspended?

o To what degree has the application been tuned to reduce its
power consumption, either in isolation or in conjunction with
other applications that might be running concurrently?

See the "POWER-OPTIMIZED APPLICATIONS" section below for more
detail on the lengths that embedded developers go to in order
to conserve power -- or, more accurately, to extend battery life.


REQUIREMENTS

o Reduce the system's power consumption in order to (1) extend
battery life and (2) preserve state until external power can
be obtained.

o It is necessary to be able to use power-oblivious applications.
Many of these applications were designed for use in PC platforms
where power consumption has historically not been of great
concern, due to either (1) the availability of external power or
(2) relatively undemanding laptop battery-lifetime expectations.
The system must be capable of running these power-oblivious
applications without requiring that these applications be
modified, and must be capable of reasonable power efficiency
even when power-oblivious applications are in use.

In other words, it must be possible to automate the incorporation
of a power-oblivious application into the Android environment,
but without significantly degrading battery lifetime.

o If the display is powered off, there is no need to run any
application whose only effect is to update the display.

Although one could simply block such an application when it next
tries to access the display, it it is highly desirable that the
application also be prevented from consuming power computing
something that will not be displayed. Furthermore, whatever
mechanism is used must operate on power-oblivious applications
that do not use blocking system calls.

There might well be similar requirements for other output-only
devices, as noted by Alan Stern.

o In order to avoid overrunning hardware and/or kernel buffers,
and to minimize response latencies, designated input events
must be delivered to the corresponding application in a timely
fashion. The application might or might not be required to
actually process the events in a timely fashion, depending on
the specific application.

In particular, if user input that would prevent the system
from entering a sleep state is received while the system is
transitioning into a sleep state, the system must transition
back out of the sleep state so that it can hand the user
input off to the corresponding application.

Other input events do not force a wakeup, and such input events
-can- be lost due to buffer overflow in hardware or the kernel.
The response latency to such input events can of course be
unbounded.

o Because Android acquires a suspend blocker as soon as an
input event is noticed and holds it until some application
reads that input event, there must be a way to cause the
suspend blocker to timeout. If there was no such timeout
facility, a power-oblivious application could block suspend by
opening an input device and then refusing to ever read from it.
(Yes, this can be considered to be a energy-efficiency bug in
the power-oblivious application. Please see the statistics
requirement below.)

o The API must provide a way for PM-driving applications that
receive events to keep themselves running until they have been
able to process those events.

o Statistics of the power-control actions taken by PM-driving
applications must be provided. Statistics are aggregated by name,
which is passed by the application in through the suspend-blocker
interface. The following specific statistics are collected in
the kernel, in roughly decreasing order of importance:

o total_time, which accumulates the total amount of time
that the corresponding suspend blocker has been held.

o active_since, which tracks how long a suspend blocker has
been held since it was last acquired, or (presumably) zero
if it is not currently held.

o count, which is the number of times that the suspend
blocker has been acquired. This is useful in combination
with total_time, as it allows you to calculate the
average hold time for the suspend blocker.

o expire_count, which is the number of times that the
suspend blocker has timed out. This indicates that
some application has an input device open, but is
not reading from it, which is a bug, as noted earlier.

o max_time, which is the longest hold time for the suspend
blocker. This allows finding cases where suspend blockers
are held for too long, but are eventually released.
(In contrast, active_since is more useful in the
held-forever case.)

o sleep_time, which is the total time that the suspend
blocker was held while the display was powered off.
(This might have interesting implications should E-ink
displays every become capable of full-motion color video,
but it is easy to imagine that the definition of "powered
off" would then include only those times during which
the display wasn't actively being updated.)

o wake_count, which is the number of times that the
suspend blocker was the first to be acquired in the
resume path. This is less than useful on some
Android platforms; Arve is dissatisfied with it
on Nexus One.

Presumably, the userspace code collects similar statistics on
application suspend-blocker activity, but that is out of the scope
of this document, which focuses instead on kernel requirements.
Given that the overhead of maintaining these statistics is
quite low, it seems that it would be worthwhile to have them
enabled in production systems, for example, in order to flag
power-buggy applications that the user has naively downloaded.

o Some PM-driving applications use power-oblivious infrastructure
code. This means that a PM-driving application must have
some way, whether explicit or implicit, to ensure that any
power-oblivious infrastructure code is permitted to run when a
PM-driving application needs it to run.

o If no PM-driving or power-optimized application are indicating
a need for the system to remain operating, the system is permitted
(even encouraged!) to suspend all execution, regardless of the
state of power-oblivious applications. (This requirement did
appear to be somewhat controversial, both in terms of what is
meant by "runnable" and in terms of what constitutes "execution".)

In Android, this is implemented by suspending even while
PM-driving or power-optimized applications are active, -unless-
a suspend blocker is held.

o Transition to system sleep state must be power-efficient.
In particular, methods based on repeated attempts to suspend
are considered to be too inefficient to be useful.

o Transition to system sleep state must occur very soon after
all PM-driving and power-optimized applications have indicated
that they have no need for the system to remain operating.
Quick transition is expecially important in cases where the wakeup
was momentary, for example, when processing sporadic network
input or processing widely spaced batches of audio output.
For an example of the latter, MP3 playback allows 1-4 minute
spacing between bursts of CPU activity).

o Individual peripherals and CPUs must still use standard
power-conservation measures, for example, transitioning CPUs into
low-power states on idle and powering down peripheral devices
and hardware accelerators that have not been recently used.

o The API that controls the system sleep state must be accessible
both from Android's Java replacement, from userland C code,
and from kernel C code (both process level and irq code, but
not NMI handlers).

o The API that controls the system sleep state must operate
correctly on SMP systems of modest size. (My guess is that
"modest" means up to four CPUs, maybe up to eight CPUs.)

o Any QoS-based solution must take display and user-input
state into account. In other words, the QoS must be expressed
as a function of the display and the user-input states.

o Transitioning to extremely low-power sleep states requires saving
and restoring DRAM and/or cache SRAM state, which in itself
consumes significant energy. The power savings must therefore
be balanced against the energy consumed in the state transitions.

o The current Android userspace API must be supported in order
to support existing device software. According to Brian
Swetland:

For Java/Dalvik apps, the wakelock API is pertty
high level -- it talks to a service via RPC (Binder)
that actually interacts with the kernel. Changing the
basic kernel<->userspace interface (within reason) is
not unthinkable. For example, Arve's suspend_blocker
patch provides a device interface rather than the proc
interface the older wakelock patches use. We'd have to
make some userspace changes to support that but they're
pretty low level and minor.

In the current model, only a few processes need to
specifically interact with the kernel (the power
management service in the system_server, possibly the
media_server and the radio interface glue). A model where
every process needs to have a bunch of instrumentation is
not very desirable from our point of view. We definitely
do need reasonable statistics in order to enable debugging
and to enable reporting to endusers (through the Battery
Usage UI) what's keeping the device awake.

o Any mechanism that freezes some subset of the applications must
ensure that none of the frozen applications hold any user-level
resources, such as pthread mutexes. The reason for this is that
freezing an application that holds a shared pthread mutex will
result in an application-level hang should some unfrozen process
attempt to acquire that same pthread mutex. Note that although
the current cgroup freezer ensures that frozen applications do not
hold any kernel-level mutexes (at least assuming these mutexes
are not wrongly held when returning to user-level execution),
it currently does nothing to prevent freezing processes holding
pthread mutexes. (There are some proposals to address this issue.)


NICE-TO-HAVES

o It would be nice to be able to identify power-oblivious
applications that never were depended on by PM-driving
applications. This particular class of power-oblivious
applications could be shut down when the screen blanks even
if some PM-driving application was preventing the system from
powering down.

There are two obstacles to meeting this requirement:

1. There must be a reliable way to identify such
applications. This should be doable, for example, the
application might be tagged by its developer.

2. There must be a reliable way to freeze them such
that no frozen application holds a resource that
might be contended by a non-frozen application.

Although the cgroup freezer does ensure that frozen
tasks hold no kernel-level resources, it currently does
nothing to ensure that no user-level resources are held.
There are some alternative proposals, which might or
might not be more successful:

a. Unfreeze this group periodically to ensure
that any such resource is eventually released,
while keeping power consumption down to a dull
roar.

b. Perform the freeze at application level, where
it is possible to determine whether an
application-level resource is held.

o Any initialization of the API that controls the system power
state should be unconditional, so as to be free from failure.
Such unconditional initialization reduces the intrusiveness of
the Android patchset.


APPARENT NON-REQUIREMENTS

o Transitioning to system sleep states need not be highly scalable,
as evidenced by the global locks. (If you believe that high
scalability will in fact be required, please provide a use case.
But please understand that I do know something about scalability
trends, but also about uses for transistors beyond more cores.)

That said, it should not be hard to provide a highly scalable
implementation of suspend blockers, especially if large systems
are allowed to take their time suspending themselves.

o Conserving power in the WiFi and cellular telephony networks.
At the moment, the focus is on increased battery life in the
handheld device, perhaps even at the expense of additional
power consumed by the externally powered WiFi and cell-telephony
equipment.

o Synchronizing wakeups of unrelated applications. This is of
course an important requirement for power savings overall, but
seems to be left to other mechanisms (e.g., timer aggregation)
by the Android folks. Although one could implement suspend
blockers so as to aggregate timers after a sufficiently long
suspension, there are problems with this approach:

o There would be a "thundering herd" problem just after
resume completed as almost every timer in the system
would expire simultaneously.

o The applications would not necessarily stay aggregated
without some other mechanism helping out.


SUGGESTED USAGE

These are constraints that the developer is expected to abide by,
"for best results" and all that.

o When a PM-driving application is preventing the system from
shutting down, and is also waiting on a power-oblivious
application, the PM-driving application should set a timeout
to handle the possibility that the power-oblivious application
might halt or otherwise fail.


POWER-OPTIMIZED APPLICATIONS

A typical power-optimized application manually controls the power state
of many separately controlled hardware subsystems to minimize power
consumption. Such optimization normally requires an understanding
of the hardware and of the full system's workload: strangely enough,
concurrently running two separately power-optimized applications often
does -not- result in a power-optimized system. Such optimization also
requires knowledge of what the application will be doing in the future,
so that needed hardware subsystems can be proactively powered up just
when the application will need them. This is especially important when
powering down cache SRAMS or banks of main memory, because such components
take significant time (and consume significant energy) when preparing them
to be powered off and when restoring their state after powering them on.

Consider an MP3 player as an example. Such a player will periodically
read MP3-encoded data from flash memory, decode it (possibly using
hardware acceleration), and place the resulting audio data into main
memory. Different systems have different ways of getting the data from
main memory to the audio output device, but let's assume that the audio
output device consumes data at a predictable rate such that the software
can use timers to schedule refilling of the device's output buffer.
The timer duration will of course need to allow for the time required to
power up the CPU and L2 cache. The timer can be allowed to happen too
soon, albeit with a battery-lifetime penalty, but cannot be permitted
to happen too late, as this will cause "skips" in the playback.

If MP3 playback is the only application running in the system, things
are quite easy. We calculate when the audio output device will empty
its buffer, allow a few milliseconds to power up the needed hardware,
and set a timer accordingly. Because modern audio output devices have
buffers that can handle roughly a second's worth of output, it is well
worthwhile to spend the few milliseconds required to flush the cache
SRAMS in order to put the system into an extremely low-power sleep state
over the several hundred milliseconds of playback.

Now suppose that this device is also recording audio -- perhaps the device
is being used to monitor an area for noise pollution, and the user is also
using the device to play music via earphones. The audio input process
will be the inverse of the audio output process: the microphone data
will fill a data buffer, which must be collected into DRAM, then encoded
(perhaps again via MP3) and stored into flash. It would be easy to create
an optimal application for audio input, but running this optimal audio
input program concurrently with the optimal audio playback program would
not necessarily result in a power-optimized combination. This lack of
optimality is due to the fact that the input and output programs would
each burn power separately powering down and up. In contrast, an optimal
solution would align the input and output programs' timers so that a
single power-down/power-up event would cover both programs' processing.
This would trade off optimal processing of each (for example, by draining
the input buffer before it was full) in order to attain global optimality
(by sharing power-down/power-up overhead).

There are a number of ways to achieve this:

1. Making the kernel group timers that occur at roughly the same
time, as has been discussed on this list many times. This can
work in many cases, but can be problematic in the audio example,
due to the presence of hard deadlines.

2. Write the programs to be aware of each other, so that each
adjusts its behavior when the other is present. This seems
to be current practice in the battery-powered embedded arena,
but is quite complex, sensitive to both hardware configuration
and software behavior, and requires that all combinations of
programs be anticipated by the designer -- which can be a serious
disadvantage given today's app stores.

3. Use new features such as range timers, so that each program
can indicate both its preference and the degree of flexibility
that it can tolerate. This also works in some cases, but as
far as I know, current proposals do not allow the kernel to take
power-consumption penalties into account.

4. Provide "heartbeat" services that allow applications to
synchronize with each other. This seems most applicable for
applications that run infrequently, such as email-checking and
location-service applications.

5. Use of hardware facilities that allow DMA to be scheduled across
time. This would allow the CPU to be turned on only for
decode/encode operations. I am under the impression that this
sort of time-based DMA hardware does exist in the embedded space
and that it is actually used for this purpose.

6. Your favorite solution here.

Whatever solution is chosen, the key point to keep in mind is that
running power-optimized applications in combination does -not- result
in optimal system behavior.


OTHER EXAMPLE APPLICATIONS

GPS application that silently displays position.

There is no point in this application consuming CPU cycles
or in powering up the GPS hardware unless the display is
active. Such an application could be handled by the Android
suspend-blocker proposal. Of course, such an application could
also periodically poll the display, shutting itself down if the
display is inactive. In this case, it would also need to have
some way to be reactivated when the display comes back on.

GPS application that alerts the user when a given location is reached.

This application should presumably run even when the display
is powered down due to input timeout. The question of whether
or not it should continue running when the device is powered
off is an interesting one that would be likely to spark much
spirited discussion. Regardless of the answer to this question,
the GPS application would hopefully run very intermittently,
adjusting the delay interval based on the device's velocity and
distance from the location in question.

I don't know enough about GPS hardware to say under what
circumstances the GPS hardware itself should be powered off.
However, my experience indicates that it takes significant
time for the GPS hardware to get a position fix after being
powered on, so presumably this decision would also be based
on device velocity and distance from the location in question.

Assuming that the application can run only intermittently,
suspend blockers would work reasonably well for this use case.
If the application needed to run continuously, battery life
would be quite short regardless of the approach used.

MP3 playback.

This requires a PM-driving (and preferably a power-optimized)
application. Because the CPU need only run intermittently,
suspend blockers can handle this use case. Presumably switching
the device off would halt playback.

Bouncing cows.

This can work with a power-oblivious application that is shut down
whenever the display is powered off or the device is switched off,
similar to the GPS application that silently displays position.


ACKNOWLEDGMENTS

Of course, just because I acknowledge their contributions does
not necessarily mean that I think they agree with my assessment
of the requirements behind suspend blockers. ;-)

Nevertheless, I am grateful for any and all feedback, whatever
the form of that feedback might be. I am new to this area, and
have much to learn.

Alan Stern
Anca Emanuel
Arjan van de Ven
Arve Hjønnevåg
Brian Swetland
David Brownell
David Lang
Florian Mickler
James Bottomley
Kevin Granade
Mark Brown
Matt Helsley
Matthew Garrett
Mikael Abrahamsson
Olivier Galibert
Paul Menage
Pavel Machek
Rafael J. Wysocki
Richard Woodruff
Ted Ts'o
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