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
 - Other resource problems such as disk load, memory bottlenecks etc.


QoS event
---------

The QoS event is generated by an element that synchronizes against the clock. It
travels upstream and contains the following fields:

 - timestamp:  The timestamp on the buffer that generated the QoS
               event. These timestamps are expressed in total running_time in
	       the sink so that the value is ever increasing.

 - jitter:     The difference of that timestamp against the current clock time.
               Negative values mean the timestamp was on time. Positive values
	       indicate the timestamp was late by that amount.

 - 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 and how the values can be used by other elements to adjust their
operations.


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 = CT - B1

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 negative, 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 positive however, the entry arrived too late in the sink 
and should therefore be dropped. J1 is the amount of time the entry was late.

Any buffer that arrives in the sink should generate a QoS event upstream.

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 ? 0 : J1)                  (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 T2 = 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 mean 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 positive 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 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 generated a buffer with timestamp B0 that arrived
in time in the sink but then received a QoS message stating B1 arrived J1
too late. This means generating B1 took (B1 + J1) - B0 = T1 - T0 = PT1, as 
given in (3). Given the buffer B1 had a duration D1 and assuming that
generating a new buffer B2 will take the same amount of processing time,
a better estimation for B2 would then be:

  B2 = T1 + D2 * DR1

 expanding gives:

  B2 = (B1 + J1) + D2 * (B1 + J1 - B0)
                        --------------  
		             D1

 assuming the durations of the frames are equal and thus D1 = D2:

  B2 = (B1 + J1) + (B1 + J1 - B0)

  B2 =  2 * (B1 + J1) - B0

 also:

  B0 = B1 - D1

 so:

  B2 =  2 * (B1 + J1) - (B1 - D1)

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

  B2 =  B1 + 2 * J1 + D1                          (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.
 - 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 are more disturbing than dropping video 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
algorithm, 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 permanently skip frames.


Demuxers
--------

Demuxers 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 process the data 
that the element pushes out.