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Original commit message from CVS: * docs/design/part-qos.txt: Fix typo. * gst/gstevent.c: * gst/gstevent.h: Update seek event docs regarding negative rates. Rename @cur to @start. * gst/gstsegment.c: (gst_segment_set_seek): * gst/gstsegment.h: Update set_seek docs regarding negative rates. Correctly update last_stop to @stop when dealing with negative rates. Rename @cur to @start. * tests/check/gst/gstpad.c: (GST_START_TEST): Activate pads before trying to use them. * tests/check/gst/gstsegment.c: (GST_START_TEST), (gst_segment_suite): Add simple check for segments and negative rates.
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 ever increasing.
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- jitter: The difference of that timestamp against the current 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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