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Original commit message from CVS: * docs/design/part-qos.txt: Bring docs in line with the code. Mostly the sign of the jitter was wrong in the docs. * gst/gstclock.c: Fix the docs for the jitter. * gst/gstevent.c: (gst_event_new_custom), (gst_event_new_tag), (gst_event_parse_tag), (gst_event_new_buffer_size), (gst_event_parse_buffer_size), (gst_event_parse_qos), (gst_event_new_seek), (gst_event_parse_seek), (gst_event_new_navigation): Make sure the GstStructure has no parent when creating custom events. Add some more argument checking so that we avoid 0.0 rates. Flesh out the docs for the QoS event some more.
297 lines
9.9 KiB
Text
297 lines
9.9 KiB
Text
Quality-of-Service
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------------------
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Quality of service is about measuring and adjusting the real-time
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performance of a pipeline.
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The real-time performance is always measured relative to the pipeline
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clock and typically happens in the sinks when they synchronize buffers
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against the clock.
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The measurements result in QOS events that aim to adjust the datarate
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in one or more upstream elements. Two types of adjustements can be
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made:
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- short time "emergency" corrections based on latest observation
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in the sinks.
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- long term rate corrections based on trends observed in the sinks.
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Sources of quality problems
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---------------------------
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- High CPU load
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- Network problems
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- Other resource problems such as disk load, memory bottlenecks etc.
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QoS event
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---------
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The QoS event travels upstream and contains the following fields:
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- timestamp: The timestamp on the buffer that generated the QoS
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event. These timestamps are expressed in total running time in
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the sink so that the value is every increasing.
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- jitter: The difference of that timestamp against the currentl clock time.
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Negative values mean the timestamp was on time. Positive values
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indicate the timestamp was late by that amount.
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- proportion: Long term prediction of the ideal rate relative to
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normal rate to get optimal quality.
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The rest of this document deals with how these values can be calculated
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in a sink and how the values can be used by other elements to adjust their
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operations.
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Collecting statistics
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---------------------
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A buffer with timestamp B1 arrives in the sink at time T1. The buffer
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timestamp is then synchronized against the clock which yields a jitter J1
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return value from the clock. The jitter J1 is simply calculated as
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J1 = CT - B1
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Where CT is the clock time when the entry arrives in the sink. This value
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is calculated inside the clock when we perform gst_clock_entry_wait().
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If the jitter is negative, the entry arrived in time and can be rendered
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after waiting for the clock to reach time B1 (which is also CT - J1).
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If the jitter is positive however, the entry arrived too late in the sink
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and should therefore be dropped. J1 is the amount of time the entry was late.
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Any buffer that arrives in the sink should generate a QoS event upstream.
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Using the jitter we can calculate the time when the buffer arrived in the
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sink:
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T1 = B1 + J1. (1)
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The time the buffer leaves the sink after synchronisation is measured as:
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T2 = B1 + (J1 < 0 ? 0 : J1) (2)
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For buffers that arrive in time (J1 < 0) the buffer leaves after synchronisation
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which is exactly B1. Late buffers (J1 >= 0) leave the sink when they arrive,
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whithout any synchronisation, which is T2 = T1 = B1 + J1.
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Using a previous T0 and a new T1, we can calculate the time it took for
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upstream to generate a buffer with timestamp B1.
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PT1 = T1 - T0 (3)
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We call PT1 the processing time needed to generate buffer with timestamp B1.
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Moreover, given the duration of the buffer D1, the current data rate (DR1) of
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the upstream element is given as:
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PT1 T1 - T0
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DR1 = --- = ------- (4)
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D1 D1
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For values 0.0 < DR1 <= 1.0 the upstream element is producing faster than
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real-time. If DR1 is exactly 1.0, the element is running at a perfect speed.
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Values DR1 > 1.0 mean that the upstream element cannot produce buffers of
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duration D1 in real-time. It is exactly DR1 that tells the amount of speedup
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we require from upstream to regain real-time performance.
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An element that is not receiving enough data is said to be starved.
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Element measurements
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--------------------
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In addition to the measurements of the datarate of the upstream element, a
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typical element must also measure its own performance. Global pipeline
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performance problems can indeed also be caused by the element itself when it
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receives too much data it cannot process in time. The element is then said to
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be flooded.
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Short term correction
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---------------------
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The timestamp and jitter serve as short term correction information
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for upstream elements. Indeed, given arrival time T1 as given in (1)
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we can be certain that buffers with a timestamp B2 < T1 will be too late
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in the sink.
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In case of a positive jitter we can therefore send a QoS message with
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a timestamp B1, jitter J1 and proportion given by (4).
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This allows an upstream element to not generate any data with a timestamps
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B2 < T1, where the element can derive T1 as B1 + J1.
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This will effectively result in frame drops.
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The element can even do a better estimation of the next valid timestamp it
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should output.
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Indeed, given the element generated a buffer with timestamp B0 that arrived
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in time in the sink but then received a QoS message stating B1 arrived J1
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too late. This means generating B1 took (B1 + J1) - B0 = T1 - T0 = PT1, as
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given in (3). Given the buffer B1 had a duration D1 and assuming that
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generating a new buffer B2 will take the same amount of processing time,
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a better estimation for B2 would then be:
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B2 = T1 + D2 * DR1
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expanding gives:
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B2 = (B1 + J1) + D2 * (B1 + J1 - B0)
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--------------
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D1
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assuming the durations of the frames are equal and thus D1 = D2:
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B2 = (B1 + J1) + (B1 + J1 - B0)
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B2 = 2 * (B1 + J1) - B0
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also:
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B0 = B1 - D1
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so:
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B2 = 2 * (B1 + J1) - (B1 - D1)
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Which yields a more accurate prediction for the next buffer given as:
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B2 = B1 + 2 * J1 + D1 (5)
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Long term correction
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--------------------
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The datarate used to calculate (5) for the short term prediction is based
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on a single observation. A more accurate datarate can be obtained by
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creating a running average over multiple datarate observations.
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This average is less susceptible to sudden changes that would only influence
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the datarate for a very short period.
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A running average is calculated over the observations given in (4) and is
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used as the proportion member in the QoS message that is sent upstream.
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Receivers of the QoS message should permanently reduce their datarate
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as given by the proportion member. Failure to do so will certainly lead to
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more dropped frames and a generally worse QoS.
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QoS strategies
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--------------
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Several strategies exist to reduce processing delay that might affect
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real time performance.
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- lowering quality
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- dropping frames (reduce CPU/bandwidth usage)
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- switch to a lower decoding/encoding quality (reduce algorithmic
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complexity)
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- switch to a lower quality source (reduce network usage)
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- increasing thread priorities
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- switch to real-time scheduling
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- assign more CPU cycles to critial pipeline parts
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- assign more CPU(s) to critical pipeline parts
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QoS implementations
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-------------------
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Here follows a small overview of how QoS can be implemented in a range of
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different types of elements.
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GstBaseSink
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-----------
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The primary implementor of QoS is GstBaseSink. It will calculate the following
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values:
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- upstream running average of processing time (5) in stream time.
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- running average of buffer durations.
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- upstream running average of processing time in system time.
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- running average of render time (in system time)
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- rendered/dropped buffers
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The processing time and the average buffer durations will be used to
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calculate a proportion.
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the processing time in system time is compared to render time to decide if
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the majority of the time is spend upstream or in the sink itself. This value
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is used to decide flood or starvation.
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the number of rendered and dropped buffers is used to query stats on the sink.
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A QoS message with the most current values is sent upstream for each buffer
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that was received by the sink.
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Normally QoS is only enabled for video pipelines. The reason being that drops
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in audio are more disturbing than dropping video frames. Also video requires in
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general more processing than audio.
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Normally there is a threshold for when buffers get dropped in a video sink. Frames
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that arrive 20 milliseconds late are still rendered as it is not noticable for
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the human eye.
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GstBaseTransform
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----------------
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Transform elements can entirely skip the transform based on the timestamp and
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jitter values of recent QoS messages since these buffers will certainly arrive
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too late.
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With any intermediate element, the element should measure its performance to
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decide if it is responsible for the quality problems or any upstream/downstream
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element.
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some transforms can reduce the complexity of their algorithms. Depending on the
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algorith, the changes in quality may have disturbing visual or audible effect
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that should be avoided.
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Video Decoders
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--------------
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A video decoder can, based on the codec in use, decide to not decode intermediate
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frames. A typical codec can for example skip the decoding of B-frames to reduce
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the CPU usage and framerate.
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If each frame is independantly decodable, any arbitrary frame can be skipped based
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on the timestamp and jitter values of the latest QoS message. In addition can the
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proportion member be used to permanently skip frames.
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Demuxers
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--------
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Demuxers usually cannot do a lot regarding QoS except for skipping frames to the next
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keyframe when a lateness QoS message arrives on a source pad.
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A demuxer can however measure if the performance problems are upstream or downstream
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and forward an updated QoS message upstream.
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Most demuxers that have multiple output pads might need to combine the QoS messages on
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all the pads and derive an aggregated QoS message for the upstream element.
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Sources
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-------
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The QoS messages only apply to push based sources since pull based sources are entirely
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controlled by another downstream element.
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Sources can receive a flood or starvation message that can be used to switch to
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less demanding source material. In case of a network stream, a switch could be done
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to a lower or higher quality stream or additional enhancement layers could be used
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or ignored.
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Live sources will automatically drop data when it takes too long to prcess the data
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that the element pushes out.
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