gstreamer/docs/design/part-qos.txt

Quality-of-Service
------------------

Quality of service is about measuring and adjusting the real-time
performance of a pipeline.

The real-time performance is always measured relative to the pipeline
clock and typically happens in the sinks when they synchronize buffers
against the clock.

The measurements result in QOS events that aim to adjust the datarate
in one or more upstream elements. Two types of adjustements can be
made:

  - short time "emergency" corrections based on latest observation
    in the sinks.
  - long term rate corrections based on trends observed in the sinks.


Sources of quality problems
---------------------------

 - High CPU load
 - Network problems


QoS event
---------

The QoS event travels upstream and contains the following fields:

 - timestamp:  The timestamp on the buffer that generated the QoS
               event
 - jitter:     The difference of that timestamp against the clock.

 - proportion: Long term prediction of the ideal rate relative to
               normal rate to get optimal quality.

The rest of this document deals with how these values can be calculated
in a sink.


Collecting statistics
---------------------

A buffer with timestamp B1 arrives in the sink at time T1. The buffer
timestamp is then synchronized against the clock which yields a jitter J1
return value from the clock. The jitter J1 is simply calculated as

  J1 = B1 - CT

Where CT is the clock time when the entry arrives in the sink. This value
is calculated inside the clock when we perform gst_clock_entry_wait().

If the jitter is positive, the entry arrived in time and can be rendered
after waiting for the clock to reach time B1 (which is also CT + J1).

If the jitter is negative however, the entry arrived too late in the sink 
and should therefore be dropped. A dropped buffer should generate a QoS
event upstream. J1 is the amount of time the entry was late.

Using the jitter we can calculate the time when the buffer arrived in the
sink: 
     
  T1 = B1 - J1.                                (1)

The time the buffer leaves the sink after synchronisation is measured as:

  T2 = B1 - (J1 < 0 ? J1 : 0)                  (2)

For buffers that arrive in time (J1 >= 0) the buffer leaves after synchronisation
which is exactly B1. Late buffers (J1 < 0) leave the sink when they arrive,
whithout any synchronisation, which is T1 = B1 - J1.

Using a previous T0 and a new T1, we can calculate the time it took for
upstream to generate a buffer with timestamp B1.

  PT1 = T1 - T0                                (3)

We call PT1 the processing time needed to generate buffer with timestamp B1.

Moreover, given the duration of the buffer D1, the current data rate (DR1) of 
the upstream element is given as:

       PT1   T1 - T0
 DR1 = --- = -------                           (4)
       D1      D1

For values 0.0 < DR1 <= 1.0 the upstream element is producing faster than
real-time. If DR1 is exactly 1.0, the element is running at a perfect speed.

Values DR1 > 1.0 means that the upstream element cannot produce buffers of
duration D1 in real-time. It is exactly DR1 that tells the amount of speedup
we require from upstream to regain real-time performance.

An element that is not receiving enough data is said to be starved.


Element measurements
--------------------

In addition to the measurements of the datarate of the upstream element, a
typical element must also measure its own performance. Global pipeline 
performance problems can indeed also be caused by the element itself when it
receives too much data it cannot process in time. The element is then said to
be flooded.


Short term correction
---------------------

The timestamp and jitter serve as short term correction information
for upstream elements. Indeed, given arrival time T1 as given in (1)
we can be certain that buffers with a timestamp B2 < T1 will be too late
in the sink.

In case of a negative jitter we can therefore send a QoS message with
a timestamp B1, jitter J1 and proportion given by (4).

This allows an upstream element to not generate any data with a timestamps
B2 < T1, where the element can derive T1 as B1 - J1.

This will effectively result in frame drops.

The element can even do a better estimation of the next valid timestamp it
should output.

Indeed, given the element generate a buffer with timestamp B1 that arrived
in time in the sink but then received a QoS message stating B2 arrived J2
too late. This means generating B2 took (B2 - J2) - B1 = T1 - T0 = PT1, as 
given in (3). Given the buffer B2 had a duration D2 and assuming that
generating a new buffer B3 will take the same amount of processing time,
a better estimation for B3 would then be:

  B3 = T1 + D3 * DR2

 expanding gives:

  B3 = (B2 - J2) + D3 * (B2 - J2 - B1)
                        --------------  
		             D2

 assuming the durations of the frames are equal and thus D2 = D3:

  B3 = (B2 - J2) + (B2 - J2 - B1)

  B3 =  2 * (B2 - J2) - B1

 also:

  B1 = B2 - D2

 so:

  B3 =  2 * (B2 - J2) - (B2 - D2)

Which yields a more accurate prediction for the next buffer given as:

  B3 =  B2 - 2 * J2 + D2                          (5)


Long term correction
--------------------

The datarate used to calculate (5) for the short term prediction is based
on a single observation. A more accurate datarate can be obtained by
creating a running average over multiple datarate observations.

This average is less susceptible to sudden changes that would only influence
the datarate for a very short period.

A running average is calculated over the observations given in (4) and is
used as the proportion member in the QoS message that is sent upstream.

Receivers of the QoS message should permanently reduce their datarate 
as given by the proportion member. Failure to do so will certainly lead to
more dropped frames and a generally worse QoS.


QoS strategies
--------------

Several strategies exist to reduce processing delay that might affect
real time performance.

 - lowering quality
   - dropping frames (reduce CPU/bandwidth usage)
   - switch to a lower decoding/encoding quality (reduce algorithmic
     complexity)
   - switch to a lower quality source (reduce network usage)
 - increasing thread priorities
   - switch to real-time scheduling
   - assign more CPU cycles to critial pipeline parts
   - assign more CPU(s) to critical pipeline parts


QoS implementations
-------------------

Here follows a small overview of how QoS can be implemented in a range of
different types of elements.


GstBaseSink
-----------

The primary implementor of QoS is GstBaseSink. It will calculate the following
values:

 - upstream running average of processing time (5) in stream time.
 - running average of buffer durations.
 - upstream running average of processing time in system time.
 - running average of render time (in system time)
 - rendered/dropped buffers

The processing time and the average buffer durations will be used to
calculate a proportion.

the processing time in system time is compared to render time to decide if
the majority of the time is spend upstream or in the sink itself. This value
is used to decide flood or starvation.

the number of rendered and dropped buffers is used to query stats on the sink.

A QoS message with the most current values is sent upstream for each buffer 
that was received by the sink.

Normally QoS is only enabled for video pipelines. The reason being that drops
in audio is more disturbing than dropping frames. Also video requires in 
general more processing than audio.

Normally there is a threshold for when buffers get dropped in a video sink. Frames
that arrive 20 milliseconds late are still rendered as it is not noticable for
the human eye.


GstBaseTransform
----------------

Transform elements can entirely skip the transform based on the timestamp and
jitter values of recent QoS messages since these buffers will certainly arrive
too late.

With any intermediate element, the element should measure its performance to
decide if it is responsible for the quality problems or any upstream/downstream
element.

some transforms can reduce the complexity of their algorithms. Depending on the
algorith, the changes in quality may have disturbing visual or audible effect 
that should be avoided.


Video Decoders
--------------

A video decoder can, based on the codec in use, decide to not decode intermediate
frames. A typical codec can for example skip the decoding of B-frames to reduce
the CPU usage and framerate.

If each frame is independantly decodable, any arbitrary frame can be skipped based
on the timestamp and jitter values of the latest QoS message. In addition can the
proportion member be used to skip frames.


Demuxers
--------

Demuxer usually cannot do a lot regarding QoS except for skipping frames to the next
keyframe when a lateness QoS message arrives on a source pad.

A demuxer can however measure if the performance problems are upstream or downstream
and forward an updated QoS message upstream.

Most demuxers that have multiple output pads might need to combine the QoS messages on
all the pads and derive an aggregated QoS message for the upstream element.


Sources
-------

The QoS messages only apply to push based sources since pull based sources are entirely
controlled by another downstream element.

Sources can receive a flood or starvation message that can be used to switch to
less demanding source material. In case of a network stream, a switch could be done
to a lower or higher quality stream or additional enhancement layers could be used
or ignored.

Live sources will automatically drop data when it takes too long to prcess the data 
that the element pushes out.