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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 adjustments can be
- short time "emergency" corrections based on latest observation
in the sinks.
- long term rate corrections based on trends observed in the sinks.
It is also possible for the application to artificially introduce delay
between synchronized buffers, this is called throttling. It can be used
to reduce the framerate, for example.
Sources of quality problems
- High CPU load
- Network problems
- Other resource problems such as disk load, memory bottlenecks etc.
- application level throttling
QoS event
The QoS event is generated by an element that synchronizes against the clock. It
travels upstream and contains the following fields:
The type of the QoS event, we have the following types and the default type
GST_QOS_TYPE_OVERFLOW: an element is receiving buffers too fast and can't
keep up processing them. Upstream should reduce the
GST_QOS_TYPE_UNDERFLOW: an element is receiving buffers too slowly and has
to drop them because they are too late. Upstream should
increase the processing rate.
GST_QOS_TYPE_THROTTLE: the application is asking to add extra delay between
buffers, upstream is allowed to drop buffers
- timestamp, G_TYPE_UINT64:
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
- jitter, G_TYPE_INT64:
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. When buffers are received in time and
throttling is not enabled, the QoS type field is set to OVERFLOW.
When throttling, the jitter contains the throttling delay added by the
application and the type is set to THROTTLE.
- proportion, G_TYPE_DOUBLE:
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
QoS message
A QOS message is posted on the bus whenever an element decides to:
- drop a buffer because of QoS reasons
- change its processing strategy because of QoS reasons (quality)
It should be expected that creating and posting the QoS message is reasonably
fast and does not significantly contribute to the QoS problems. Options to
disable this feature could also be presented on elements.
This message can be posted by a sink/src that performs synchronisation against the
clock (live) or it could be posted by an upstream element that performs QoS
because of QOS events received from a downstream element (!live).
The GST_MESSAGE_QOS contains at least the following info:
If the QoS message was dropped by a live element such as a sink or a live
source. If the live property is FALSE, the QoS message was generated as a
response to a QoS event in a non-live element.
- running-time, G_TYPE_UINT64:
The running_time of the buffer that generated the QoS message.
- stream-time, G_TYPE_UINT64:
The stream_time of the buffer that generated the QoS message.
- timestamp, G_TYPE_UINT64:
The timestamp of the buffer that generated the QoS message.
- duration, G_TYPE_UINT64:
The duration of the buffer that generated the QoS message.
- jitter, G_TYPE_INT64:
The difference of the running-time against the deadline. Negative
values mean the timestamp was on time. Positive values indicate the
timestamp was late (and dropped) by that amount. The deadline can be
a realtime running_time or an estimated running_time.
- proportion, G_TYPE_DOUBLE:
Long term prediction of the ideal rate relative to normal rate to get
optimal quality.
- quality, G_TYPE_INT:
An element dependent integer value that specifies the current quality
level of the element. The default maximum quality is 1000000.
Units of the 'processed' and 'dropped' fields. Video sinks and video
filters will use GST_FORMAT_BUFFERS (frames). Audio sinks and audio filters
will likely use GST_FORMAT_DEFAULT (samples).
- processed: G_TYPE_UINT64:
Total number of units correctly processed since the last state change to
READY or a flushing operation.
- dropped: G_TYPE_UINT64:
Total number of units dropped since the last state change to READY or a
flushing operation.
The 'running-time' and 'processed' fields can be used to estimate the average
processing rate (framerate for video).
Elements might add additional fields in the message which are documented in the
relevant elements or baseclasses.
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_id_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
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 underflowed.
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 overflowed.
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 event 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 event 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)
assuming the durations of the frames are equal and thus D1 = D2:
B2 = (B1 + J1) + (B1 + J1 - B0)
B2 = 2 * (B1 + J1) - B0
B0 = B1 - D1
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 event that is sent upstream.
Receivers of the QoS event 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.
In throttle mode, the time distance between buffers is kept to a configurable
throttle interval. This means that effectively the buffer rate is limited
to 1 buffer per throttle interval. This can be used to limit the framerate,
for example.
When an element is configured in throttling mode (this is usually only
implemented on sinks) it should produce QoS events upstream with the jitter
field set to the throttle interval. This should instruct upstream elements to
skip or drop the remaining buffers in the configured throttle interval.
The proportion field is set to the desired slowdown needed to get the
desired throttle interval. Implementations can use the QoS Throttle type,
the proportion and the jitter member to tune their implementations.
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
- 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.
The primary implementor of QoS is GstBaseSink. It will calculate the following
- 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 overflow or underflow.
The number of rendered and dropped buffers is used to query stats on the sink.
A QoS event 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 noticeable for
the human eye.
A QoS message is posted whenever a (part of a) buffer is dropped.
In throttle mode, the sink sends QoS event upstream with the timestamp set to
the running_time of the latest buffer and the jitter set to the throttle interval.
If the throttled buffer is late, the lateness is subtracted from the throttle
interval in order to keep the desired throttle interval.
Transform elements can entirely skip the transform based on the timestamp and
jitter values of recent QoS event 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
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.
A QoS message should be posted when a frame is dropped or when the quality
of the filter is reduced. The quality member in the QOS message should reflect
the quality setting of the filter.
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 event. In addition can the
proportion member be used to permanently skip frames.
It is suggested to adjust the quality field of the QoS message with the expected
amount of dropped frames (skipping B and/or P frames). This depends on the
particular spacing of B and P frames in the stream. If the quality control would
result in half of the frames to be dropped (typical B frame skipping), the
quality field would be set to 1000000 * 1/2 = 500000. If a typical I frame spacing
of 18 frames is used, skipping B and P frames would result in 17 dropped frames
or 1 decoded frame every 18 frames. The quality member should be set to
1000000 * 1/18 = 55555.
- skipping B frames: quality = 500000
- skipping P/B frames: quality = 55555 (for I-frame spacing of 18 frames)
Demuxers usually cannot do a lot regarding QoS except for skipping frames to the next
keyframe when a lateness QoS event arrives on a source pad.
A demuxer can however measure if the performance problems are upstream or downstream
and forward an updated QoS event upstream.
Most demuxers that have multiple output pads might need to combine the QoS
events on all the pads and derive an aggregated QoS event for the upstream element.
The QoS events only apply to push based sources since pull based sources are entirely
controlled by another downstream element.
Sources can receive a overflow or underflow event 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.
Live sources should post a QoS message when data is dropped.