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Side by Side Diff: webrtc/modules/congestion_controller/trendline_estimator.h

Issue 2582513002: Revert of Avoid precision loss in TrendlineEstimator from int64_t -> double conversion (Closed)
Patch Set: Created 4 years ago
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1 /* 1 /*
2 * Copyright (c) 2016 The WebRTC project authors. All Rights Reserved. 2 * Copyright (c) 2016 The WebRTC project authors. All Rights Reserved.
3 * 3 *
4 * Use of this source code is governed by a BSD-style license 4 * Use of this source code is governed by a BSD-style license
5 * that can be found in the LICENSE file in the root of the source 5 * that can be found in the LICENSE file in the root of the source
6 * tree. An additional intellectual property rights grant can be found 6 * tree. An additional intellectual property rights grant can be found
7 * in the file PATENTS. All contributing project authors may 7 * in the file PATENTS. All contributing project authors may
8 * be found in the AUTHORS file in the root of the source tree. 8 * be found in the AUTHORS file in the root of the source tree.
9 */ 9 */
10 #ifndef WEBRTC_MODULES_CONGESTION_CONTROLLER_TRENDLINE_ESTIMATOR_H_ 10 #ifndef WEBRTC_MODULES_CONGESTION_CONTROLLER_TRENDLINE_ESTIMATOR_H_
11 #define WEBRTC_MODULES_CONGESTION_CONTROLLER_TRENDLINE_ESTIMATOR_H_ 11 #define WEBRTC_MODULES_CONGESTION_CONTROLLER_TRENDLINE_ESTIMATOR_H_
12 12
13 #include <stddef.h>
14 #include <stdint.h>
15
16 #include <list> 13 #include <list>
17 #include <utility> 14 #include <utility>
18 15
19 #include "webrtc/base/constructormagic.h" 16 #include "webrtc/base/constructormagic.h"
17 #include "webrtc/common_types.h"
20 18
21 namespace webrtc { 19 namespace webrtc {
22 20
23 class TrendlineEstimator { 21 class TrendlineEstimator {
24 public: 22 public:
25 // |window_size| is the number of points required to compute a trend line. 23 // |window_size| is the number of points required to compute a trend line.
26 // |smoothing_coef| controls how much we smooth out the delay before fitting 24 // |smoothing_coef| controls how much we smooth out the delay before fitting
27 // the trend line. |threshold_gain| is used to scale the trendline slope for 25 // the trend line. |threshold_gain| is used to scale the trendline slope for
28 // comparison to the old threshold. Once the old estimator has been removed 26 // comparison to the old threshold. Once the old estimator has been removed
29 // (or the thresholds been merged into the estimators), we can just set the 27 // (or the thresholds been merged into the estimators), we can just set the
30 // threshold instead of setting a gain. 28 // threshold instead of setting a gain.
31 TrendlineEstimator(size_t window_size, 29 TrendlineEstimator(size_t window_size,
32 double smoothing_coef, 30 double smoothing_coef,
33 double threshold_gain); 31 double threshold_gain);
34 ~TrendlineEstimator(); 32 ~TrendlineEstimator();
35 33
36 // Update the estimator with a new sample. The deltas should represent deltas 34 // Update the estimator with a new sample. The deltas should represent deltas
37 // between timestamp groups as defined by the InterArrival class. 35 // between timestamp groups as defined by the InterArrival class.
38 void Update(double recv_delta_ms, 36 void Update(double recv_delta_ms, double send_delta_ms, double now_ms);
39 double send_delta_ms,
40 int64_t arrival_time_ms);
41 37
42 // Returns the estimated trend k multiplied by some gain. 38 // Returns the estimated trend k multiplied by some gain.
43 // 0 < k < 1 -> the delay increases, queues are filling up 39 // 0 < k < 1 -> the delay increases, queues are filling up
44 // k == 0 -> the delay does not change 40 // k == 0 -> the delay does not change
45 // k < 0 -> the delay decreases, queues are being emptied 41 // k < 0 -> the delay decreases, queues are being emptied
46 double trendline_slope() const { return trendline_ * threshold_gain_; } 42 double trendline_slope() const { return trendline_ * threshold_gain_; }
47 43
48 // Returns the number of deltas which the current estimator state is based on. 44 // Returns the number of deltas which the current estimator state is based on.
49 unsigned int num_of_deltas() const { return num_of_deltas_; } 45 unsigned int num_of_deltas() const { return num_of_deltas_; }
50 46
51 private: 47 private:
52 // Parameters. 48 // Parameters.
53 const size_t window_size_; 49 const size_t window_size_;
54 const double smoothing_coef_; 50 const double smoothing_coef_;
55 const double threshold_gain_; 51 const double threshold_gain_;
56 // Used by the existing threshold. 52 // Used by the existing threshold.
57 unsigned int num_of_deltas_; 53 unsigned int num_of_deltas_;
58 // Keep the arrival times small by using the change from the first packet.
59 int64_t first_arrival_time_ms;
60 // Exponential backoff filtering. 54 // Exponential backoff filtering.
61 double accumulated_delay_; 55 double accumulated_delay_;
62 double smoothed_delay_; 56 double smoothed_delay_;
63 // Linear least squares regression. 57 // Linear least squares regression.
64 std::list<std::pair<double, double>> delay_hist_; 58 std::list<std::pair<double, double>> delay_hist_;
65 double trendline_; 59 double trendline_;
66 60
67 RTC_DISALLOW_COPY_AND_ASSIGN(TrendlineEstimator); 61 RTC_DISALLOW_COPY_AND_ASSIGN(TrendlineEstimator);
68 }; 62 };
69 } // namespace webrtc 63 } // namespace webrtc
70 64
71 #endif // WEBRTC_MODULES_CONGESTION_CONTROLLER_TRENDLINE_ESTIMATOR_H_ 65 #endif // WEBRTC_MODULES_CONGESTION_CONTROLLER_TRENDLINE_ESTIMATOR_H_
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