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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.
*/
#ifndef MODULES_CONGESTION_CONTROLLER_GOOG_CC_TRENDLINE_ESTIMATOR_H_
#define MODULES_CONGESTION_CONTROLLER_GOOG_CC_TRENDLINE_ESTIMATOR_H_
#include <stddef.h>
#include <stdint.h>
#include <deque>
#include <utility>
#include "modules/congestion_controller/goog_cc/delay_increase_detector_interface.h"
#include "rtc_base/constructormagic.h"
namespace webrtc {
namespace webrtc_cc {
class TrendlineEstimator : public DelayIncreaseDetectorInterface {
public:
// |window_size| is the number of points required to compute a trend line.
// |smoothing_coef| controls how much we smooth out the delay before fitting
// the trend line. |threshold_gain| is used to scale the trendline slope for
// comparison to the old threshold. Once the old estimator has been removed
// (or the thresholds been merged into the estimators), we can just set the
// threshold instead of setting a gain.
TrendlineEstimator(size_t window_size,
double smoothing_coef,
double threshold_gain);
~TrendlineEstimator() override;
// Update the estimator with a new sample. The deltas should represent deltas
// between timestamp groups as defined by the InterArrival class.
void Update(double recv_delta_ms,
double send_delta_ms,
int64_t arrival_time_ms) override;
BandwidthUsage State() const override;
// Returns the estimated trend k multiplied by some gain.
// 0 < k < 1 -> the delay increases, queues are filling up
// k == 0 -> the delay does not change
// k < 0 -> the delay decreases, queues are being emptied
double trendline_slope() const { return trendline_ * threshold_gain_; }
// Returns the number of deltas which the current estimator state is based on.
unsigned int num_of_deltas() const { return num_of_deltas_; }
private:
void Detect(double offset,
double ts_delta,
int num_of_deltas,
int64_t now_ms);
void UpdateThreshold(double modified_offset, int64_t now_ms);
// Parameters.
const size_t window_size_;
const double smoothing_coef_;
const double threshold_gain_;
// Used by the existing threshold.
unsigned int num_of_deltas_;
// Keep the arrival times small by using the change from the first packet.
int64_t first_arrival_time_ms_;
// Exponential backoff filtering.
double accumulated_delay_;
double smoothed_delay_;
// Linear least squares regression.
std::deque<std::pair<double, double>> delay_hist_;
double trendline_;
const double k_up_;
const double k_down_;
double overusing_time_threshold_;
double threshold_;
int64_t last_update_ms_;
double prev_offset_;
double time_over_using_;
int overuse_counter_;
BandwidthUsage hypothesis_;
RTC_DISALLOW_COPY_AND_ASSIGN(TrendlineEstimator);
};
} // namespace webrtc_cc
} // namespace webrtc
#endif // MODULES_CONGESTION_CONTROLLER_GOOG_CC_TRENDLINE_ESTIMATOR_H_