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 /* * Copyright (c) 2016 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/congestion_controller/trendline_estimator.h" #include #include "webrtc/api/optional.h" #include "webrtc/modules/remote_bitrate_estimator/test/bwe_test_logging.h" #include "webrtc/rtc_base/checks.h" namespace webrtc { namespace { rtc::Optional LinearFitSlope( const std::deque>& points) { RTC_DCHECK(points.size() >= 2); // Compute the "center of mass". double sum_x = 0; double sum_y = 0; for (const auto& point : points) { sum_x += point.first; sum_y += point.second; } double x_avg = sum_x / points.size(); double y_avg = sum_y / points.size(); // Compute the slope k = \sum (x_i-x_avg)(y_i-y_avg) / \sum (x_i-x_avg)^2 double numerator = 0; double denominator = 0; for (const auto& point : points) { numerator += (point.first - x_avg) * (point.second - y_avg); denominator += (point.first - x_avg) * (point.first - x_avg); } if (denominator == 0) return rtc::Optional(); return rtc::Optional(numerator / denominator); } } // namespace enum { kDeltaCounterMax = 1000 }; TrendlineEstimator::TrendlineEstimator(size_t window_size, double smoothing_coef, double threshold_gain) : window_size_(window_size), smoothing_coef_(smoothing_coef), threshold_gain_(threshold_gain), num_of_deltas_(0), first_arrival_time_ms(-1), accumulated_delay_(0), smoothed_delay_(0), delay_hist_(), trendline_(0) {} TrendlineEstimator::~TrendlineEstimator() {} void TrendlineEstimator::Update(double recv_delta_ms, double send_delta_ms, int64_t arrival_time_ms) { const double delta_ms = recv_delta_ms - send_delta_ms; ++num_of_deltas_; if (num_of_deltas_ > kDeltaCounterMax) num_of_deltas_ = kDeltaCounterMax; if (first_arrival_time_ms == -1) first_arrival_time_ms = arrival_time_ms; // Exponential backoff filter. accumulated_delay_ += delta_ms; BWE_TEST_LOGGING_PLOT(1, "accumulated_delay_ms", arrival_time_ms, accumulated_delay_); smoothed_delay_ = smoothing_coef_ * smoothed_delay_ + (1 - smoothing_coef_) * accumulated_delay_; BWE_TEST_LOGGING_PLOT(1, "smoothed_delay_ms", arrival_time_ms, smoothed_delay_); // Simple linear regression. delay_hist_.push_back(std::make_pair( static_cast(arrival_time_ms - first_arrival_time_ms), smoothed_delay_)); if (delay_hist_.size() > window_size_) delay_hist_.pop_front(); if (delay_hist_.size() == window_size_) { // Only update trendline_ if it is possible to fit a line to the data. trendline_ = LinearFitSlope(delay_hist_).value_or(trendline_); } BWE_TEST_LOGGING_PLOT(1, "trendline_slope", arrival_time_ms, trendline_); } } // namespace webrtc