| Index: webrtc/modules/congestion_controller/delay_based_bwe.cc
|
| diff --git a/webrtc/modules/congestion_controller/delay_based_bwe.cc b/webrtc/modules/congestion_controller/delay_based_bwe.cc
|
| index 8f8618190c103946f534ca5cc5a43701ff316729..8fcb8baf77e415d1aaff449be0402f9c8a97ff41 100644
|
| --- a/webrtc/modules/congestion_controller/delay_based_bwe.cc
|
| +++ b/webrtc/modules/congestion_controller/delay_based_bwe.cc
|
| @@ -42,7 +42,7 @@ constexpr int kInitialRateWindowMs = 500;
|
| constexpr int kRateWindowMs = 150;
|
|
|
| // Parameters for linear least squares fit of regression line to noisy data.
|
| -constexpr size_t kDefaultTrendlineWindowSize = 15;
|
| +constexpr size_t kDefaultTrendlineWindowSize = 20;
|
| constexpr double kDefaultTrendlineSmoothingCoeff = 0.9;
|
| constexpr double kDefaultTrendlineThresholdGain = 4.0;
|
|
|
| @@ -53,20 +53,12 @@ constexpr double kDefaultMedianSlopeThresholdGain = 4.0;
|
| constexpr int kMaxConsecutiveFailedLookups = 5;
|
|
|
| const char kBitrateEstimateExperiment[] = "WebRTC-ImprovedBitrateEstimate";
|
| -const char kBweTrendlineFilterExperiment[] = "WebRTC-BweTrendlineFilter";
|
| const char kBweMedianSlopeFilterExperiment[] = "WebRTC-BweMedianSlopeFilter";
|
|
|
| bool BitrateEstimateExperimentIsEnabled() {
|
| return webrtc::field_trial::IsEnabled(kBitrateEstimateExperiment);
|
| }
|
|
|
| -bool TrendlineFilterExperimentIsEnabled() {
|
| - std::string experiment_string =
|
| - webrtc::field_trial::FindFullName(kBweTrendlineFilterExperiment);
|
| - // The experiment is enabled iff the field trial string begins with "Enabled".
|
| - return experiment_string.find("Enabled") == 0;
|
| -}
|
| -
|
| bool MedianSlopeFilterExperimentIsEnabled() {
|
| std::string experiment_string =
|
| webrtc::field_trial::FindFullName(kBweMedianSlopeFilterExperiment);
|
| @@ -74,36 +66,8 @@ bool MedianSlopeFilterExperimentIsEnabled() {
|
| return experiment_string.find("Enabled") == 0;
|
| }
|
|
|
| -bool ReadTrendlineFilterExperimentParameters(size_t* window_size,
|
| - double* smoothing_coef,
|
| - double* threshold_gain) {
|
| - RTC_DCHECK(TrendlineFilterExperimentIsEnabled());
|
| - RTC_DCHECK(!MedianSlopeFilterExperimentIsEnabled());
|
| - RTC_DCHECK(window_size != nullptr);
|
| - RTC_DCHECK(smoothing_coef != nullptr);
|
| - RTC_DCHECK(threshold_gain != nullptr);
|
| - std::string experiment_string =
|
| - webrtc::field_trial::FindFullName(kBweTrendlineFilterExperiment);
|
| - int parsed_values = sscanf(experiment_string.c_str(), "Enabled-%zu,%lf,%lf",
|
| - window_size, smoothing_coef, threshold_gain);
|
| - if (parsed_values == 3) {
|
| - RTC_CHECK_GT(*window_size, 1) << "Need at least 2 points to fit a line.";
|
| - RTC_CHECK(0 <= *smoothing_coef && *smoothing_coef <= 1)
|
| - << "Coefficient needs to be between 0 and 1 for weighted average.";
|
| - RTC_CHECK_GT(*threshold_gain, 0) << "Threshold gain needs to be positive.";
|
| - return true;
|
| - }
|
| - LOG(LS_WARNING) << "Failed to parse parameters for BweTrendlineFilter "
|
| - "experiment from field trial string. Using default.";
|
| - *window_size = kDefaultTrendlineWindowSize;
|
| - *smoothing_coef = kDefaultTrendlineSmoothingCoeff;
|
| - *threshold_gain = kDefaultTrendlineThresholdGain;
|
| - return false;
|
| -}
|
| -
|
| bool ReadMedianSlopeFilterExperimentParameters(size_t* window_size,
|
| double* threshold_gain) {
|
| - RTC_DCHECK(!TrendlineFilterExperimentIsEnabled());
|
| RTC_DCHECK(MedianSlopeFilterExperimentIsEnabled());
|
| RTC_DCHECK(window_size != nullptr);
|
| RTC_DCHECK(threshold_gain != nullptr);
|
| @@ -231,12 +195,10 @@ rtc::Optional<uint32_t> DelayBasedBwe::BitrateEstimator::bitrate_bps() const {
|
| }
|
|
|
| DelayBasedBwe::DelayBasedBwe(RtcEventLog* event_log, const Clock* clock)
|
| - : in_trendline_experiment_(TrendlineFilterExperimentIsEnabled()),
|
| - in_median_slope_experiment_(MedianSlopeFilterExperimentIsEnabled()),
|
| + : in_median_slope_experiment_(MedianSlopeFilterExperimentIsEnabled()),
|
| event_log_(event_log),
|
| clock_(clock),
|
| inter_arrival_(),
|
| - kalman_estimator_(),
|
| trendline_estimator_(),
|
| detector_(),
|
| receiver_incoming_bitrate_(),
|
| @@ -252,23 +214,14 @@ DelayBasedBwe::DelayBasedBwe(RtcEventLog* event_log, const Clock* clock)
|
| consecutive_delayed_feedbacks_(0),
|
| last_logged_bitrate_(0),
|
| last_logged_state_(kBwNormal) {
|
| - if (in_trendline_experiment_) {
|
| - ReadTrendlineFilterExperimentParameters(&trendline_window_size_,
|
| - &trendline_smoothing_coeff_,
|
| - &trendline_threshold_gain_);
|
| - LOG(LS_INFO) << "Trendline filter experiment enabled with parameters "
|
| - << trendline_window_size_ << ',' << trendline_smoothing_coeff_
|
| - << ',' << trendline_threshold_gain_;
|
| - }
|
| if (in_median_slope_experiment_) {
|
| ReadMedianSlopeFilterExperimentParameters(&median_slope_window_size_,
|
| &median_slope_threshold_gain_);
|
| LOG(LS_INFO) << "Median-slope filter experiment enabled with parameters "
|
| << median_slope_window_size_ << ','
|
| << median_slope_threshold_gain_;
|
| - }
|
| - if (!in_trendline_experiment_ && !in_median_slope_experiment_) {
|
| - LOG(LS_INFO) << "No overuse experiment enabled. Using Kalman filter.";
|
| + } else {
|
| + LOG(LS_INFO) << "No overuse experiment enabled. Using Trendline filter.";
|
| }
|
|
|
| network_thread_.DetachFromThread();
|
| @@ -342,7 +295,6 @@ DelayBasedBwe::Result DelayBasedBwe::IncomingPacketFeedback(
|
| inter_arrival_.reset(
|
| new InterArrival((kTimestampGroupLengthMs << kInterArrivalShift) / 1000,
|
| kTimestampToMs, true));
|
| - kalman_estimator_.reset(new OveruseEstimator(OverUseDetectorOptions()));
|
| trendline_estimator_.reset(new TrendlineEstimator(
|
| trendline_window_size_, trendline_smoothing_coeff_,
|
| trendline_threshold_gain_));
|
| @@ -369,24 +321,17 @@ DelayBasedBwe::Result DelayBasedBwe::IncomingPacketFeedback(
|
| now_ms, packet_feedback.payload_size,
|
| &ts_delta, &t_delta, &size_delta)) {
|
| double ts_delta_ms = (1000.0 * ts_delta) / (1 << kInterArrivalShift);
|
| - if (in_trendline_experiment_) {
|
| - trendline_estimator_->Update(t_delta, ts_delta_ms,
|
| - packet_feedback.arrival_time_ms);
|
| - detector_.Detect(trendline_estimator_->trendline_slope(), ts_delta_ms,
|
| - trendline_estimator_->num_of_deltas(),
|
| - packet_feedback.arrival_time_ms);
|
| - } else if (in_median_slope_experiment_) {
|
| + if (in_median_slope_experiment_) {
|
| median_slope_estimator_->Update(t_delta, ts_delta_ms,
|
| packet_feedback.arrival_time_ms);
|
| detector_.Detect(median_slope_estimator_->trendline_slope(), ts_delta_ms,
|
| median_slope_estimator_->num_of_deltas(),
|
| packet_feedback.arrival_time_ms);
|
| } else {
|
| - kalman_estimator_->Update(t_delta, ts_delta_ms, size_delta,
|
| - detector_.State(),
|
| - packet_feedback.arrival_time_ms);
|
| - detector_.Detect(kalman_estimator_->offset(), ts_delta_ms,
|
| - kalman_estimator_->num_of_deltas(),
|
| + trendline_estimator_->Update(t_delta, ts_delta_ms,
|
| + packet_feedback.arrival_time_ms);
|
| + detector_.Detect(trendline_estimator_->trendline_slope(), ts_delta_ms,
|
| + trendline_estimator_->num_of_deltas(),
|
| packet_feedback.arrival_time_ms);
|
| }
|
| }
|
|
|