|  | /* | 
|  | *  Copyright (c) 2011 The WebRTC project authors. All Rights Reserved. | 
|  | * | 
|  | *  Use of this source code is governed by a BSD-style license | 
|  | *  that can be found in the LICENSE file in the root of the source | 
|  | *  tree. An additional intellectual property rights grant can be found | 
|  | *  in the file PATENTS.  All contributing project authors may | 
|  | *  be found in the AUTHORS file in the root of the source tree. | 
|  | */ | 
|  |  | 
|  | #include "webrtc/modules/video_coding/main/source/internal_defines.h" | 
|  | #include "webrtc/modules/video_coding/main/source/jitter_estimator.h" | 
|  | #include "webrtc/modules/video_coding/main/source/rtt_filter.h" | 
|  | #include "webrtc/system_wrappers/interface/clock.h" | 
|  | #include "webrtc/system_wrappers/interface/field_trial.h" | 
|  |  | 
|  | #include <assert.h> | 
|  | #include <math.h> | 
|  | #include <stdlib.h> | 
|  | #include <string.h> | 
|  |  | 
|  | namespace webrtc { | 
|  |  | 
|  | enum { kStartupDelaySamples = 30 }; | 
|  | enum { kFsAccuStartupSamples = 5 }; | 
|  | enum { kMaxFramerateEstimate = 200 }; | 
|  |  | 
|  | VCMJitterEstimator::VCMJitterEstimator(const Clock* clock, | 
|  | int32_t vcmId, | 
|  | int32_t receiverId) | 
|  | : _vcmId(vcmId), | 
|  | _receiverId(receiverId), | 
|  | _phi(0.97), | 
|  | _psi(0.9999), | 
|  | _alphaCountMax(400), | 
|  | _thetaLow(0.000001), | 
|  | _nackLimit(3), | 
|  | _numStdDevDelayOutlier(15), | 
|  | _numStdDevFrameSizeOutlier(3), | 
|  | _noiseStdDevs(2.33),       // ~Less than 1% chance | 
|  | // (look up in normal distribution table)... | 
|  | _noiseStdDevOffset(30.0),  // ...of getting 30 ms freezes | 
|  | _rttFilter(), | 
|  | fps_counter_(30),  // TODO(sprang): Use an estimator with limit based on | 
|  | // time, rather than number of samples. | 
|  | low_rate_experiment_(kInit), | 
|  | clock_(clock) { | 
|  | Reset(); | 
|  | } | 
|  |  | 
|  | VCMJitterEstimator::~VCMJitterEstimator() { | 
|  | } | 
|  |  | 
|  | VCMJitterEstimator& | 
|  | VCMJitterEstimator::operator=(const VCMJitterEstimator& rhs) | 
|  | { | 
|  | if (this != &rhs) | 
|  | { | 
|  | memcpy(_thetaCov, rhs._thetaCov, sizeof(_thetaCov)); | 
|  | memcpy(_Qcov, rhs._Qcov, sizeof(_Qcov)); | 
|  |  | 
|  | _vcmId = rhs._vcmId; | 
|  | _receiverId = rhs._receiverId; | 
|  | _avgFrameSize = rhs._avgFrameSize; | 
|  | _varFrameSize = rhs._varFrameSize; | 
|  | _maxFrameSize = rhs._maxFrameSize; | 
|  | _fsSum = rhs._fsSum; | 
|  | _fsCount = rhs._fsCount; | 
|  | _lastUpdateT = rhs._lastUpdateT; | 
|  | _prevEstimate = rhs._prevEstimate; | 
|  | _prevFrameSize = rhs._prevFrameSize; | 
|  | _avgNoise = rhs._avgNoise; | 
|  | _alphaCount = rhs._alphaCount; | 
|  | _filterJitterEstimate = rhs._filterJitterEstimate; | 
|  | _startupCount = rhs._startupCount; | 
|  | _latestNackTimestamp = rhs._latestNackTimestamp; | 
|  | _nackCount = rhs._nackCount; | 
|  | _rttFilter = rhs._rttFilter; | 
|  | } | 
|  | return *this; | 
|  | } | 
|  |  | 
|  | // Resets the JitterEstimate | 
|  | void | 
|  | VCMJitterEstimator::Reset() | 
|  | { | 
|  | _theta[0] = 1/(512e3/8); | 
|  | _theta[1] = 0; | 
|  | _varNoise = 4.0; | 
|  |  | 
|  | _thetaCov[0][0] = 1e-4; | 
|  | _thetaCov[1][1] = 1e2; | 
|  | _thetaCov[0][1] = _thetaCov[1][0] = 0; | 
|  | _Qcov[0][0] = 2.5e-10; | 
|  | _Qcov[1][1] = 1e-10; | 
|  | _Qcov[0][1] = _Qcov[1][0] = 0; | 
|  | _avgFrameSize = 500; | 
|  | _maxFrameSize = 500; | 
|  | _varFrameSize = 100; | 
|  | _lastUpdateT = -1; | 
|  | _prevEstimate = -1.0; | 
|  | _prevFrameSize = 0; | 
|  | _avgNoise = 0.0; | 
|  | _alphaCount = 1; | 
|  | _filterJitterEstimate = 0.0; | 
|  | _latestNackTimestamp = 0; | 
|  | _nackCount = 0; | 
|  | _fsSum = 0; | 
|  | _fsCount = 0; | 
|  | _startupCount = 0; | 
|  | _rttFilter.Reset(); | 
|  | fps_counter_.Reset(); | 
|  | } | 
|  |  | 
|  | void | 
|  | VCMJitterEstimator::ResetNackCount() | 
|  | { | 
|  | _nackCount = 0; | 
|  | } | 
|  |  | 
|  | // Updates the estimates with the new measurements | 
|  | void | 
|  | VCMJitterEstimator::UpdateEstimate(int64_t frameDelayMS, uint32_t frameSizeBytes, | 
|  | bool incompleteFrame /* = false */) | 
|  | { | 
|  | if (frameSizeBytes == 0) | 
|  | { | 
|  | return; | 
|  | } | 
|  | int deltaFS = frameSizeBytes - _prevFrameSize; | 
|  | if (_fsCount < kFsAccuStartupSamples) | 
|  | { | 
|  | _fsSum += frameSizeBytes; | 
|  | _fsCount++; | 
|  | } | 
|  | else if (_fsCount == kFsAccuStartupSamples) | 
|  | { | 
|  | // Give the frame size filter | 
|  | _avgFrameSize = static_cast<double>(_fsSum) / | 
|  | static_cast<double>(_fsCount); | 
|  | _fsCount++; | 
|  | } | 
|  | if (!incompleteFrame || frameSizeBytes > _avgFrameSize) | 
|  | { | 
|  | double avgFrameSize = _phi * _avgFrameSize + | 
|  | (1 - _phi) * frameSizeBytes; | 
|  | if (frameSizeBytes < _avgFrameSize + 2 * sqrt(_varFrameSize)) | 
|  | { | 
|  | // Only update the average frame size if this sample wasn't a | 
|  | // key frame | 
|  | _avgFrameSize = avgFrameSize; | 
|  | } | 
|  | // Update the variance anyway since we want to capture cases where we only get | 
|  | // key frames. | 
|  | _varFrameSize = VCM_MAX(_phi * _varFrameSize + (1 - _phi) * | 
|  | (frameSizeBytes - avgFrameSize) * | 
|  | (frameSizeBytes - avgFrameSize), 1.0); | 
|  | } | 
|  |  | 
|  | // Update max frameSize estimate | 
|  | _maxFrameSize = VCM_MAX(_psi * _maxFrameSize, static_cast<double>(frameSizeBytes)); | 
|  |  | 
|  | if (_prevFrameSize == 0) | 
|  | { | 
|  | _prevFrameSize = frameSizeBytes; | 
|  | return; | 
|  | } | 
|  | _prevFrameSize = frameSizeBytes; | 
|  |  | 
|  | // Only update the Kalman filter if the sample is not considered | 
|  | // an extreme outlier. Even if it is an extreme outlier from a | 
|  | // delay point of view, if the frame size also is large the | 
|  | // deviation is probably due to an incorrect line slope. | 
|  | double deviation = DeviationFromExpectedDelay(frameDelayMS, deltaFS); | 
|  |  | 
|  | if (fabs(deviation) < _numStdDevDelayOutlier * sqrt(_varNoise) || | 
|  | frameSizeBytes > _avgFrameSize + _numStdDevFrameSizeOutlier * sqrt(_varFrameSize)) | 
|  | { | 
|  | // Update the variance of the deviation from the | 
|  | // line given by the Kalman filter | 
|  | EstimateRandomJitter(deviation, incompleteFrame); | 
|  | // Prevent updating with frames which have been congested by a large | 
|  | // frame, and therefore arrives almost at the same time as that frame. | 
|  | // This can occur when we receive a large frame (key frame) which | 
|  | // has been delayed. The next frame is of normal size (delta frame), | 
|  | // and thus deltaFS will be << 0. This removes all frame samples | 
|  | // which arrives after a key frame. | 
|  | if ((!incompleteFrame || deviation >= 0.0) && | 
|  | static_cast<double>(deltaFS) > - 0.25 * _maxFrameSize) | 
|  | { | 
|  | // Update the Kalman filter with the new data | 
|  | KalmanEstimateChannel(frameDelayMS, deltaFS); | 
|  | } | 
|  | } | 
|  | else | 
|  | { | 
|  | int nStdDev = (deviation >= 0) ? _numStdDevDelayOutlier : -_numStdDevDelayOutlier; | 
|  | EstimateRandomJitter(nStdDev * sqrt(_varNoise), incompleteFrame); | 
|  | } | 
|  | // Post process the total estimated jitter | 
|  | if (_startupCount >= kStartupDelaySamples) | 
|  | { | 
|  | PostProcessEstimate(); | 
|  | } | 
|  | else | 
|  | { | 
|  | _startupCount++; | 
|  | } | 
|  | } | 
|  |  | 
|  | // Updates the nack/packet ratio | 
|  | void | 
|  | VCMJitterEstimator::FrameNacked() | 
|  | { | 
|  | // Wait until _nackLimit retransmissions has been received, | 
|  | // then always add ~1 RTT delay. | 
|  | // TODO(holmer): Should we ever remove the additional delay if the | 
|  | // the packet losses seem to have stopped? We could for instance scale | 
|  | // the number of RTTs to add with the amount of retransmissions in a given | 
|  | // time interval, or similar. | 
|  | if (_nackCount < _nackLimit) | 
|  | { | 
|  | _nackCount++; | 
|  | } | 
|  | } | 
|  |  | 
|  | // Updates Kalman estimate of the channel | 
|  | // The caller is expected to sanity check the inputs. | 
|  | void | 
|  | VCMJitterEstimator::KalmanEstimateChannel(int64_t frameDelayMS, | 
|  | int32_t deltaFSBytes) | 
|  | { | 
|  | double Mh[2]; | 
|  | double hMh_sigma; | 
|  | double kalmanGain[2]; | 
|  | double measureRes; | 
|  | double t00, t01; | 
|  |  | 
|  | // Kalman filtering | 
|  |  | 
|  | // Prediction | 
|  | // M = M + Q | 
|  | _thetaCov[0][0] += _Qcov[0][0]; | 
|  | _thetaCov[0][1] += _Qcov[0][1]; | 
|  | _thetaCov[1][0] += _Qcov[1][0]; | 
|  | _thetaCov[1][1] += _Qcov[1][1]; | 
|  |  | 
|  | // Kalman gain | 
|  | // K = M*h'/(sigma2n + h*M*h') = M*h'/(1 + h*M*h') | 
|  | // h = [dFS 1] | 
|  | // Mh = M*h' | 
|  | // hMh_sigma = h*M*h' + R | 
|  | Mh[0] = _thetaCov[0][0] * deltaFSBytes + _thetaCov[0][1]; | 
|  | Mh[1] = _thetaCov[1][0] * deltaFSBytes + _thetaCov[1][1]; | 
|  | // sigma weights measurements with a small deltaFS as noisy and | 
|  | // measurements with large deltaFS as good | 
|  | if (_maxFrameSize < 1.0) | 
|  | { | 
|  | return; | 
|  | } | 
|  | double sigma = (300.0 * exp(-fabs(static_cast<double>(deltaFSBytes)) / | 
|  | (1e0 * _maxFrameSize)) + 1) * sqrt(_varNoise); | 
|  | if (sigma < 1.0) | 
|  | { | 
|  | sigma = 1.0; | 
|  | } | 
|  | hMh_sigma = deltaFSBytes * Mh[0] + Mh[1] + sigma; | 
|  | if ((hMh_sigma < 1e-9 && hMh_sigma >= 0) || (hMh_sigma > -1e-9 && hMh_sigma <= 0)) | 
|  | { | 
|  | assert(false); | 
|  | return; | 
|  | } | 
|  | kalmanGain[0] = Mh[0] / hMh_sigma; | 
|  | kalmanGain[1] = Mh[1] / hMh_sigma; | 
|  |  | 
|  | // Correction | 
|  | // theta = theta + K*(dT - h*theta) | 
|  | measureRes = frameDelayMS - (deltaFSBytes * _theta[0] + _theta[1]); | 
|  | _theta[0] += kalmanGain[0] * measureRes; | 
|  | _theta[1] += kalmanGain[1] * measureRes; | 
|  |  | 
|  | if (_theta[0] < _thetaLow) | 
|  | { | 
|  | _theta[0] = _thetaLow; | 
|  | } | 
|  |  | 
|  | // M = (I - K*h)*M | 
|  | t00 = _thetaCov[0][0]; | 
|  | t01 = _thetaCov[0][1]; | 
|  | _thetaCov[0][0] = (1 - kalmanGain[0] * deltaFSBytes) * t00 - | 
|  | kalmanGain[0] * _thetaCov[1][0]; | 
|  | _thetaCov[0][1] = (1 - kalmanGain[0] * deltaFSBytes) * t01 - | 
|  | kalmanGain[0] * _thetaCov[1][1]; | 
|  | _thetaCov[1][0] = _thetaCov[1][0] * (1 - kalmanGain[1]) - | 
|  | kalmanGain[1] * deltaFSBytes * t00; | 
|  | _thetaCov[1][1] = _thetaCov[1][1] * (1 - kalmanGain[1]) - | 
|  | kalmanGain[1] * deltaFSBytes * t01; | 
|  |  | 
|  | // Covariance matrix, must be positive semi-definite | 
|  | assert(_thetaCov[0][0] + _thetaCov[1][1] >= 0 && | 
|  | _thetaCov[0][0] * _thetaCov[1][1] - _thetaCov[0][1] * _thetaCov[1][0] >= 0 && | 
|  | _thetaCov[0][0] >= 0); | 
|  | } | 
|  |  | 
|  | // Calculate difference in delay between a sample and the | 
|  | // expected delay estimated by the Kalman filter | 
|  | double | 
|  | VCMJitterEstimator::DeviationFromExpectedDelay(int64_t frameDelayMS, | 
|  | int32_t deltaFSBytes) const | 
|  | { | 
|  | return frameDelayMS - (_theta[0] * deltaFSBytes + _theta[1]); | 
|  | } | 
|  |  | 
|  | // Estimates the random jitter by calculating the variance of the | 
|  | // sample distance from the line given by theta. | 
|  | void VCMJitterEstimator::EstimateRandomJitter(double d_dT, | 
|  | bool incompleteFrame) { | 
|  | uint64_t now = clock_->TimeInMicroseconds(); | 
|  | if (_lastUpdateT != -1) { | 
|  | fps_counter_.AddSample(now - _lastUpdateT); | 
|  | } | 
|  | _lastUpdateT = now; | 
|  |  | 
|  | if (_alphaCount == 0) { | 
|  | assert(false); | 
|  | return; | 
|  | } | 
|  | double alpha = | 
|  | static_cast<double>(_alphaCount - 1) / static_cast<double>(_alphaCount); | 
|  | _alphaCount++; | 
|  | if (_alphaCount > _alphaCountMax) | 
|  | _alphaCount = _alphaCountMax; | 
|  |  | 
|  | if (LowRateExperimentEnabled()) { | 
|  | // In order to avoid a low frame rate stream to react slower to changes, | 
|  | // scale the alpha weight relative a 30 fps stream. | 
|  | double fps = GetFrameRate(); | 
|  | if (fps > 0.0) { | 
|  | double rate_scale = 30.0 / fps; | 
|  | // At startup, there can be a lot of noise in the fps estimate. | 
|  | // Interpolate rate_scale linearly, from 1.0 at sample #1, to 30.0 / fps | 
|  | // at sample #kStartupDelaySamples. | 
|  | if (_alphaCount < kStartupDelaySamples) { | 
|  | rate_scale = | 
|  | (_alphaCount * rate_scale + (kStartupDelaySamples - _alphaCount)) / | 
|  | kStartupDelaySamples; | 
|  | } | 
|  | alpha = pow(alpha, rate_scale); | 
|  | } | 
|  | } | 
|  |  | 
|  | double avgNoise = alpha * _avgNoise + (1 - alpha) * d_dT; | 
|  | double varNoise = | 
|  | alpha * _varNoise + (1 - alpha) * (d_dT - _avgNoise) * (d_dT - _avgNoise); | 
|  | if (!incompleteFrame || varNoise > _varNoise) { | 
|  | _avgNoise = avgNoise; | 
|  | _varNoise = varNoise; | 
|  | } | 
|  | if (_varNoise < 1.0) { | 
|  | // The variance should never be zero, since we might get | 
|  | // stuck and consider all samples as outliers. | 
|  | _varNoise = 1.0; | 
|  | } | 
|  | } | 
|  |  | 
|  | double | 
|  | VCMJitterEstimator::NoiseThreshold() const | 
|  | { | 
|  | double noiseThreshold = _noiseStdDevs * sqrt(_varNoise) - _noiseStdDevOffset; | 
|  | if (noiseThreshold < 1.0) | 
|  | { | 
|  | noiseThreshold = 1.0; | 
|  | } | 
|  | return noiseThreshold; | 
|  | } | 
|  |  | 
|  | // Calculates the current jitter estimate from the filtered estimates | 
|  | double | 
|  | VCMJitterEstimator::CalculateEstimate() | 
|  | { | 
|  | double ret = _theta[0] * (_maxFrameSize - _avgFrameSize) + NoiseThreshold(); | 
|  |  | 
|  | // A very low estimate (or negative) is neglected | 
|  | if (ret < 1.0) { | 
|  | if (_prevEstimate <= 0.01) | 
|  | { | 
|  | ret = 1.0; | 
|  | } | 
|  | else | 
|  | { | 
|  | ret = _prevEstimate; | 
|  | } | 
|  | } | 
|  | if (ret > 10000.0) // Sanity | 
|  | { | 
|  | ret = 10000.0; | 
|  | } | 
|  | _prevEstimate = ret; | 
|  | return ret; | 
|  | } | 
|  |  | 
|  | void | 
|  | VCMJitterEstimator::PostProcessEstimate() | 
|  | { | 
|  | _filterJitterEstimate = CalculateEstimate(); | 
|  | } | 
|  |  | 
|  | void | 
|  | VCMJitterEstimator::UpdateRtt(uint32_t rttMs) | 
|  | { | 
|  | _rttFilter.Update(rttMs); | 
|  | } | 
|  |  | 
|  | void | 
|  | VCMJitterEstimator::UpdateMaxFrameSize(uint32_t frameSizeBytes) | 
|  | { | 
|  | if (_maxFrameSize < frameSizeBytes) | 
|  | { | 
|  | _maxFrameSize = frameSizeBytes; | 
|  | } | 
|  | } | 
|  |  | 
|  | // Returns the current filtered estimate if available, | 
|  | // otherwise tries to calculate an estimate. | 
|  | int VCMJitterEstimator::GetJitterEstimate(double rttMultiplier) { | 
|  | double jitterMS = CalculateEstimate() + OPERATING_SYSTEM_JITTER; | 
|  | if (_filterJitterEstimate > jitterMS) | 
|  | jitterMS = _filterJitterEstimate; | 
|  | if (_nackCount >= _nackLimit) | 
|  | jitterMS += _rttFilter.RttMs() * rttMultiplier; | 
|  |  | 
|  | if (LowRateExperimentEnabled()) { | 
|  | static const double kJitterScaleLowThreshold = 5.0; | 
|  | static const double kJitterScaleHighThreshold = 10.0; | 
|  | double fps = GetFrameRate(); | 
|  | // Ignore jitter for very low fps streams. | 
|  | if (fps < kJitterScaleLowThreshold) { | 
|  | if (fps == 0.0) { | 
|  | return jitterMS; | 
|  | } | 
|  | return 0; | 
|  | } | 
|  |  | 
|  | // Semi-low frame rate; scale by factor linearly interpolated from 0.0 at | 
|  | // kJitterScaleLowThreshold to 1.0 at kJitterScaleHighThreshold. | 
|  | if (fps < kJitterScaleHighThreshold) { | 
|  | jitterMS = | 
|  | (1.0 / (kJitterScaleHighThreshold - kJitterScaleLowThreshold)) * | 
|  | (fps - kJitterScaleLowThreshold) * jitterMS; | 
|  | } | 
|  | } | 
|  |  | 
|  | return static_cast<uint32_t>(jitterMS + 0.5); | 
|  | } | 
|  |  | 
|  | bool VCMJitterEstimator::LowRateExperimentEnabled() { | 
|  | if (low_rate_experiment_ == kInit) { | 
|  | std::string group = | 
|  | webrtc::field_trial::FindFullName("WebRTC-ReducedJitterDelay"); | 
|  | if (group == "Disabled") { | 
|  | low_rate_experiment_ = kDisabled; | 
|  | } else { | 
|  | low_rate_experiment_ = kEnabled; | 
|  | } | 
|  | } | 
|  | return low_rate_experiment_ == kEnabled ? true : false; | 
|  | } | 
|  |  | 
|  | double VCMJitterEstimator::GetFrameRate() const { | 
|  | if (fps_counter_.count() == 0) | 
|  | return 0; | 
|  |  | 
|  | double fps = 1000000.0 / fps_counter_.ComputeMean(); | 
|  | // Sanity check. | 
|  | assert(fps >= 0.0); | 
|  | if (fps > kMaxFramerateEstimate) { | 
|  | fps = kMaxFramerateEstimate; | 
|  | } | 
|  | return fps; | 
|  | } | 
|  |  | 
|  | } |