| /* |
| * Copyright 2021 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 "modules/congestion_controller/goog_cc/loss_based_bwe_v2.h" |
| |
| #include <algorithm> |
| #include <cmath> |
| #include <cstddef> |
| #include <cstdlib> |
| #include <limits> |
| #include <utility> |
| #include <vector> |
| |
| #include "absl/algorithm/container.h" |
| #include "absl/types/optional.h" |
| #include "api/array_view.h" |
| #include "api/transport/network_types.h" |
| #include "api/transport/webrtc_key_value_config.h" |
| #include "api/units/data_rate.h" |
| #include "api/units/data_size.h" |
| #include "api/units/time_delta.h" |
| #include "api/units/timestamp.h" |
| #include "rtc_base/experiments/field_trial_list.h" |
| #include "rtc_base/experiments/field_trial_parser.h" |
| #include "rtc_base/logging.h" |
| |
| namespace webrtc { |
| |
| namespace { |
| |
| bool IsValid(DataRate datarate) { |
| return datarate.IsFinite(); |
| } |
| |
| bool IsValid(Timestamp timestamp) { |
| return timestamp.IsFinite(); |
| } |
| |
| struct PacketResultsSummary { |
| int num_packets = 0; |
| int num_lost_packets = 0; |
| DataSize total_size = DataSize::Zero(); |
| Timestamp first_send_time = Timestamp::PlusInfinity(); |
| Timestamp last_send_time = Timestamp::MinusInfinity(); |
| }; |
| |
| // Returns a `PacketResultsSummary` where `first_send_time` is `PlusInfinity, |
| // and `last_send_time` is `MinusInfinity`, if `packet_results` is empty. |
| PacketResultsSummary GetPacketResultsSummary( |
| rtc::ArrayView<const PacketResult> packet_results) { |
| PacketResultsSummary packet_results_summary; |
| |
| packet_results_summary.num_packets = packet_results.size(); |
| for (const PacketResult& packet : packet_results) { |
| if (!packet.IsReceived()) { |
| packet_results_summary.num_lost_packets++; |
| } |
| packet_results_summary.total_size += packet.sent_packet.size; |
| packet_results_summary.first_send_time = std::min( |
| packet_results_summary.first_send_time, packet.sent_packet.send_time); |
| packet_results_summary.last_send_time = std::max( |
| packet_results_summary.last_send_time, packet.sent_packet.send_time); |
| } |
| |
| return packet_results_summary; |
| } |
| |
| double GetLossProbability(double inherent_loss, |
| DataRate loss_limited_bandwidth, |
| DataRate sending_rate) { |
| if (inherent_loss < 0.0 || inherent_loss > 1.0) { |
| RTC_LOG(LS_WARNING) << "The inherent loss must be in [0,1]: " |
| << inherent_loss; |
| inherent_loss = std::min(std::max(inherent_loss, 0.0), 1.0); |
| } |
| if (!sending_rate.IsFinite()) { |
| RTC_LOG(LS_WARNING) << "The sending rate must be finite: " |
| << ToString(sending_rate); |
| } |
| if (!loss_limited_bandwidth.IsFinite()) { |
| RTC_LOG(LS_WARNING) << "The loss limited bandwidth must be finite: " |
| << ToString(loss_limited_bandwidth); |
| } |
| |
| // We approximate the loss model |
| // loss_probability = inherent_loss + (1 - inherent_loss) * |
| // max(0, sending_rate - bandwidth) / sending_rate |
| // by |
| // loss_probability = inherent_loss + |
| // max(0, sending_rate - bandwidth) / sending_rate |
| // as it allows for simpler calculations and makes little difference in |
| // practice. |
| double loss_probability = inherent_loss; |
| if (IsValid(sending_rate) && IsValid(loss_limited_bandwidth) && |
| (sending_rate > loss_limited_bandwidth)) { |
| loss_probability += (sending_rate - loss_limited_bandwidth) / sending_rate; |
| } |
| return std::min(std::max(loss_probability, 1.0e-6), 1.0 - 1.0e-6); |
| } |
| |
| } // namespace |
| |
| LossBasedBweV2::LossBasedBweV2(const WebRtcKeyValueConfig* key_value_config) |
| : config_(CreateConfig(key_value_config)) { |
| if (!config_.has_value()) { |
| RTC_LOG(LS_VERBOSE) << "The configuration does not specify that the " |
| "estimator should be enabled, disabling it."; |
| return; |
| } |
| if (!IsConfigValid()) { |
| RTC_LOG(LS_WARNING) |
| << "The configuration is not valid, disabling the estimator."; |
| config_.reset(); |
| return; |
| } |
| |
| current_estimate_.inherent_loss = config_->initial_inherent_loss_estimate; |
| observations_.resize(config_->observation_window_size); |
| temporal_weights_.resize(config_->observation_window_size); |
| instant_upper_bound_temporal_weights_.resize( |
| config_->observation_window_size); |
| CalculateTemporalWeights(); |
| } |
| |
| bool LossBasedBweV2::IsEnabled() const { |
| return config_.has_value(); |
| } |
| |
| bool LossBasedBweV2::IsReady() const { |
| return IsEnabled() && IsValid(current_estimate_.loss_limited_bandwidth) && |
| num_observations_ > 0; |
| } |
| |
| DataRate LossBasedBweV2::GetBandwidthEstimate() const { |
| if (!IsReady()) { |
| if (!IsEnabled()) { |
| RTC_LOG(LS_WARNING) |
| << "The estimator must be enabled before it can be used."; |
| } else { |
| if (!IsValid(current_estimate_.loss_limited_bandwidth)) { |
| RTC_LOG(LS_WARNING) |
| << "The estimator must be initialized before it can be used."; |
| } |
| if (num_observations_ <= 0) { |
| RTC_LOG(LS_WARNING) << "The estimator must receive enough loss " |
| "statistics before it can be used."; |
| } |
| } |
| return DataRate::PlusInfinity(); |
| } |
| |
| return std::min(current_estimate_.loss_limited_bandwidth, |
| GetInstantUpperBound()); |
| } |
| |
| void LossBasedBweV2::SetAcknowledgedBitrate(DataRate acknowledged_bitrate) { |
| if (IsValid(acknowledged_bitrate)) { |
| acknowledged_bitrate_ = acknowledged_bitrate; |
| } else { |
| RTC_LOG(LS_WARNING) << "The acknowledged bitrate must be finite: " |
| << ToString(acknowledged_bitrate); |
| } |
| } |
| |
| void LossBasedBweV2::SetBandwidthEstimate(DataRate bandwidth_estimate) { |
| if (IsValid(bandwidth_estimate)) { |
| current_estimate_.loss_limited_bandwidth = bandwidth_estimate; |
| } else { |
| RTC_LOG(LS_WARNING) << "The bandwidth estimate must be finite: " |
| << ToString(bandwidth_estimate); |
| } |
| } |
| |
| void LossBasedBweV2::UpdateBandwidthEstimate( |
| rtc::ArrayView<const PacketResult> packet_results, |
| DataRate delay_based_estimate) { |
| if (!IsEnabled()) { |
| RTC_LOG(LS_WARNING) |
| << "The estimator must be enabled before it can be used."; |
| return; |
| } |
| if (packet_results.empty()) { |
| RTC_LOG(LS_VERBOSE) |
| << "The estimate cannot be updated without any loss statistics."; |
| return; |
| } |
| |
| if (!PushBackObservation(packet_results)) { |
| return; |
| } |
| |
| if (!IsValid(current_estimate_.loss_limited_bandwidth)) { |
| RTC_LOG(LS_VERBOSE) |
| << "The estimator must be initialized before it can be used."; |
| return; |
| } |
| |
| ChannelParameters best_candidate = current_estimate_; |
| double objective_max = std::numeric_limits<double>::lowest(); |
| for (ChannelParameters candidate : GetCandidates(delay_based_estimate)) { |
| NewtonsMethodUpdate(candidate); |
| |
| const double candidate_objective = GetObjective(candidate); |
| if (candidate_objective > objective_max) { |
| objective_max = candidate_objective; |
| best_candidate = candidate; |
| } |
| } |
| if (best_candidate.loss_limited_bandwidth < |
| current_estimate_.loss_limited_bandwidth) { |
| last_time_estimate_reduced_ = last_send_time_most_recent_observation_; |
| } |
| current_estimate_ = best_candidate; |
| } |
| |
| // Returns a `LossBasedBweV2::Config` iff the `key_value_config` specifies a |
| // configuration for the `LossBasedBweV2` which is explicitly enabled. |
| absl::optional<LossBasedBweV2::Config> LossBasedBweV2::CreateConfig( |
| const WebRtcKeyValueConfig* key_value_config) { |
| FieldTrialParameter<bool> enabled("Enabled", false); |
| FieldTrialParameter<double> bandwidth_rampup_upper_bound_factor( |
| "BwRampupUpperBoundFactor", 1.1); |
| FieldTrialParameter<double> rampup_acceleration_max_factor( |
| "BwRampupAccelMaxFactor", 0.0); |
| FieldTrialParameter<TimeDelta> rampup_acceleration_maxout_time( |
| "BwRampupAccelMaxoutTime", TimeDelta::Seconds(60)); |
| FieldTrialList<double> candidate_factors("CandidateFactors", |
| {1.05, 1.0, 0.95}); |
| FieldTrialParameter<double> higher_bandwidth_bias_factor("HigherBwBiasFactor", |
| 0.00001); |
| FieldTrialParameter<double> higher_log_bandwidth_bias_factor( |
| "HigherLogBwBiasFactor", 0.001); |
| FieldTrialParameter<double> inherent_loss_lower_bound( |
| "InherentLossLowerBound", 1.0e-3); |
| FieldTrialParameter<DataRate> inherent_loss_upper_bound_bandwidth_balance( |
| "InherentLossUpperBoundBwBalance", DataRate::KilobitsPerSec(15.0)); |
| FieldTrialParameter<double> inherent_loss_upper_bound_offset( |
| "InherentLossUpperBoundOffset", 0.05); |
| FieldTrialParameter<double> initial_inherent_loss_estimate( |
| "InitialInherentLossEstimate", 0.01); |
| FieldTrialParameter<int> newton_iterations("NewtonIterations", 1); |
| FieldTrialParameter<double> newton_step_size("NewtonStepSize", 0.5); |
| FieldTrialParameter<bool> append_acknowledged_rate_candidate( |
| "AckedRateCandidate", true); |
| FieldTrialParameter<bool> append_delay_based_estimate_candidate( |
| "DelayBasedCandidate", false); |
| FieldTrialParameter<TimeDelta> observation_duration_lower_bound( |
| "ObservationDurationLowerBound", TimeDelta::Seconds(1)); |
| FieldTrialParameter<int> observation_window_size("ObservationWindowSize", 20); |
| FieldTrialParameter<double> sending_rate_smoothing_factor( |
| "SendingRateSmoothingFactor", 0.0); |
| FieldTrialParameter<double> instant_upper_bound_temporal_weight_factor( |
| "InstantUpperBoundTemporalWeightFactor", 0.99); |
| FieldTrialParameter<DataRate> instant_upper_bound_bandwidth_balance( |
| "InstantUpperBoundBwBalance", DataRate::KilobitsPerSec(15.0)); |
| FieldTrialParameter<double> instant_upper_bound_loss_offset( |
| "InstantUpperBoundLossOffset", 0.05); |
| FieldTrialParameter<double> temporal_weight_factor("TemporalWeightFactor", |
| 0.99); |
| |
| if (key_value_config) { |
| ParseFieldTrial({&enabled, |
| &bandwidth_rampup_upper_bound_factor, |
| &rampup_acceleration_max_factor, |
| &rampup_acceleration_maxout_time, |
| &candidate_factors, |
| &higher_bandwidth_bias_factor, |
| &higher_log_bandwidth_bias_factor, |
| &inherent_loss_lower_bound, |
| &inherent_loss_upper_bound_bandwidth_balance, |
| &inherent_loss_upper_bound_offset, |
| &initial_inherent_loss_estimate, |
| &newton_iterations, |
| &newton_step_size, |
| &append_acknowledged_rate_candidate, |
| &append_delay_based_estimate_candidate, |
| &observation_duration_lower_bound, |
| &observation_window_size, |
| &sending_rate_smoothing_factor, |
| &instant_upper_bound_temporal_weight_factor, |
| &instant_upper_bound_bandwidth_balance, |
| &instant_upper_bound_loss_offset, |
| &temporal_weight_factor}, |
| key_value_config->Lookup("WebRTC-Bwe-LossBasedBweV2")); |
| } |
| |
| absl::optional<Config> config; |
| if (!enabled.Get()) { |
| return config; |
| } |
| config.emplace(); |
| config->bandwidth_rampup_upper_bound_factor = |
| bandwidth_rampup_upper_bound_factor.Get(); |
| config->rampup_acceleration_max_factor = rampup_acceleration_max_factor.Get(); |
| config->rampup_acceleration_maxout_time = |
| rampup_acceleration_maxout_time.Get(); |
| config->candidate_factors = candidate_factors.Get(); |
| config->higher_bandwidth_bias_factor = higher_bandwidth_bias_factor.Get(); |
| config->higher_log_bandwidth_bias_factor = |
| higher_log_bandwidth_bias_factor.Get(); |
| config->inherent_loss_lower_bound = inherent_loss_lower_bound.Get(); |
| config->inherent_loss_upper_bound_bandwidth_balance = |
| inherent_loss_upper_bound_bandwidth_balance.Get(); |
| config->inherent_loss_upper_bound_offset = |
| inherent_loss_upper_bound_offset.Get(); |
| config->initial_inherent_loss_estimate = initial_inherent_loss_estimate.Get(); |
| config->newton_iterations = newton_iterations.Get(); |
| config->newton_step_size = newton_step_size.Get(); |
| config->append_acknowledged_rate_candidate = |
| append_acknowledged_rate_candidate.Get(); |
| config->append_delay_based_estimate_candidate = |
| append_delay_based_estimate_candidate.Get(); |
| config->observation_duration_lower_bound = |
| observation_duration_lower_bound.Get(); |
| config->observation_window_size = observation_window_size.Get(); |
| config->sending_rate_smoothing_factor = sending_rate_smoothing_factor.Get(); |
| config->instant_upper_bound_temporal_weight_factor = |
| instant_upper_bound_temporal_weight_factor.Get(); |
| config->instant_upper_bound_bandwidth_balance = |
| instant_upper_bound_bandwidth_balance.Get(); |
| config->instant_upper_bound_loss_offset = |
| instant_upper_bound_loss_offset.Get(); |
| config->temporal_weight_factor = temporal_weight_factor.Get(); |
| return config; |
| } |
| |
| bool LossBasedBweV2::IsConfigValid() const { |
| if (!config_.has_value()) { |
| return false; |
| } |
| |
| bool valid = true; |
| |
| if (config_->bandwidth_rampup_upper_bound_factor <= 1.0) { |
| RTC_LOG(LS_WARNING) |
| << "The bandwidth rampup upper bound factor must be greater than 1: " |
| << config_->bandwidth_rampup_upper_bound_factor; |
| valid = false; |
| } |
| if (config_->rampup_acceleration_max_factor < 0.0) { |
| RTC_LOG(LS_WARNING) |
| << "The rampup acceleration max factor must be non-negative.: " |
| << config_->rampup_acceleration_max_factor; |
| valid = false; |
| } |
| if (config_->rampup_acceleration_maxout_time <= TimeDelta::Zero()) { |
| RTC_LOG(LS_WARNING) |
| << "The rampup acceleration maxout time must be above zero: " |
| << config_->rampup_acceleration_maxout_time.seconds(); |
| valid = false; |
| } |
| for (double candidate_factor : config_->candidate_factors) { |
| if (candidate_factor <= 0.0) { |
| RTC_LOG(LS_WARNING) << "All candidate factors must be greater than zero: " |
| << candidate_factor; |
| valid = false; |
| } |
| } |
| |
| // Ensure that the configuration allows generation of at least one candidate |
| // other than the current estimate. |
| if (!config_->append_acknowledged_rate_candidate && |
| !config_->append_delay_based_estimate_candidate && |
| !absl::c_any_of(config_->candidate_factors, |
| [](double cf) { return cf != 1.0; })) { |
| RTC_LOG(LS_WARNING) |
| << "The configuration does not allow generating candidates. Specify " |
| "a candidate factor other than 1.0, allow the acknowledged rate " |
| "to be a candidate, and/or allow the delay based estimate to be a " |
| "candidate."; |
| valid = false; |
| } |
| |
| if (config_->higher_bandwidth_bias_factor < 0.0) { |
| RTC_LOG(LS_WARNING) |
| << "The higher bandwidth bias factor must be non-negative: " |
| << config_->higher_bandwidth_bias_factor; |
| valid = false; |
| } |
| if (config_->inherent_loss_lower_bound < 0.0 || |
| config_->inherent_loss_lower_bound >= 1.0) { |
| RTC_LOG(LS_WARNING) << "The inherent loss lower bound must be in [0, 1): " |
| << config_->inherent_loss_lower_bound; |
| valid = false; |
| } |
| if (config_->inherent_loss_upper_bound_bandwidth_balance <= |
| DataRate::Zero()) { |
| RTC_LOG(LS_WARNING) |
| << "The inherent loss upper bound bandwidth balance " |
| "must be positive: " |
| << ToString(config_->inherent_loss_upper_bound_bandwidth_balance); |
| valid = false; |
| } |
| if (config_->inherent_loss_upper_bound_offset < |
| config_->inherent_loss_lower_bound || |
| config_->inherent_loss_upper_bound_offset >= 1.0) { |
| RTC_LOG(LS_WARNING) << "The inherent loss upper bound must be greater " |
| "than or equal to the inherent " |
| "loss lower bound, which is " |
| << config_->inherent_loss_lower_bound |
| << ", and less than 1: " |
| << config_->inherent_loss_upper_bound_offset; |
| valid = false; |
| } |
| if (config_->initial_inherent_loss_estimate < 0.0 || |
| config_->initial_inherent_loss_estimate >= 1.0) { |
| RTC_LOG(LS_WARNING) |
| << "The initial inherent loss estimate must be in [0, 1): " |
| << config_->initial_inherent_loss_estimate; |
| valid = false; |
| } |
| if (config_->newton_iterations <= 0) { |
| RTC_LOG(LS_WARNING) << "The number of Newton iterations must be positive: " |
| << config_->newton_iterations; |
| valid = false; |
| } |
| if (config_->newton_step_size <= 0.0) { |
| RTC_LOG(LS_WARNING) << "The Newton step size must be positive: " |
| << config_->newton_step_size; |
| valid = false; |
| } |
| if (config_->observation_duration_lower_bound <= TimeDelta::Zero()) { |
| RTC_LOG(LS_WARNING) |
| << "The observation duration lower bound must be positive: " |
| << ToString(config_->observation_duration_lower_bound); |
| valid = false; |
| } |
| if (config_->observation_window_size < 2) { |
| RTC_LOG(LS_WARNING) << "The observation window size must be at least 2: " |
| << config_->observation_window_size; |
| valid = false; |
| } |
| if (config_->sending_rate_smoothing_factor < 0.0 || |
| config_->sending_rate_smoothing_factor >= 1.0) { |
| RTC_LOG(LS_WARNING) |
| << "The sending rate smoothing factor must be in [0, 1): " |
| << config_->sending_rate_smoothing_factor; |
| valid = false; |
| } |
| if (config_->instant_upper_bound_temporal_weight_factor <= 0.0 || |
| config_->instant_upper_bound_temporal_weight_factor > 1.0) { |
| RTC_LOG(LS_WARNING) |
| << "The instant upper bound temporal weight factor must be in (0, 1]" |
| << config_->instant_upper_bound_temporal_weight_factor; |
| valid = false; |
| } |
| if (config_->instant_upper_bound_bandwidth_balance <= DataRate::Zero()) { |
| RTC_LOG(LS_WARNING) |
| << "The instant upper bound bandwidth balance must be positive: " |
| << ToString(config_->instant_upper_bound_bandwidth_balance); |
| valid = false; |
| } |
| if (config_->instant_upper_bound_loss_offset < 0.0 || |
| config_->instant_upper_bound_loss_offset >= 1.0) { |
| RTC_LOG(LS_WARNING) |
| << "The instant upper bound loss offset must be in [0, 1): " |
| << config_->instant_upper_bound_loss_offset; |
| valid = false; |
| } |
| if (config_->temporal_weight_factor <= 0.0 || |
| config_->temporal_weight_factor > 1.0) { |
| RTC_LOG(LS_WARNING) << "The temporal weight factor must be in (0, 1]: " |
| << config_->temporal_weight_factor; |
| valid = false; |
| } |
| |
| return valid; |
| } |
| |
| double LossBasedBweV2::GetAverageReportedLossRatio() const { |
| if (num_observations_ <= 0) { |
| return 0.0; |
| } |
| |
| int num_packets = 0; |
| int num_lost_packets = 0; |
| for (const Observation& observation : observations_) { |
| if (!observation.IsInitialized()) { |
| continue; |
| } |
| |
| double instant_temporal_weight = |
| instant_upper_bound_temporal_weights_[(num_observations_ - 1) - |
| observation.id]; |
| num_packets += instant_temporal_weight * observation.num_packets; |
| num_lost_packets += instant_temporal_weight * observation.num_lost_packets; |
| } |
| |
| return static_cast<double>(num_lost_packets) / num_packets; |
| } |
| |
| DataRate LossBasedBweV2::GetCandidateBandwidthUpperBound() const { |
| if (!acknowledged_bitrate_.has_value()) |
| return DataRate::PlusInfinity(); |
| |
| DataRate candidate_bandwidth_upper_bound = |
| config_->bandwidth_rampup_upper_bound_factor * (*acknowledged_bitrate_); |
| |
| if (config_->rampup_acceleration_max_factor > 0.0) { |
| const TimeDelta time_since_bandwidth_reduced = std::min( |
| config_->rampup_acceleration_maxout_time, |
| std::max(TimeDelta::Zero(), last_send_time_most_recent_observation_ - |
| last_time_estimate_reduced_)); |
| const double rampup_acceleration = config_->rampup_acceleration_max_factor * |
| time_since_bandwidth_reduced / |
| config_->rampup_acceleration_maxout_time; |
| |
| candidate_bandwidth_upper_bound += |
| rampup_acceleration * (*acknowledged_bitrate_); |
| } |
| return candidate_bandwidth_upper_bound; |
| } |
| |
| std::vector<LossBasedBweV2::ChannelParameters> LossBasedBweV2::GetCandidates( |
| DataRate delay_based_estimate) const { |
| std::vector<DataRate> bandwidths; |
| for (double candidate_factor : config_->candidate_factors) { |
| bandwidths.push_back(candidate_factor * |
| current_estimate_.loss_limited_bandwidth); |
| } |
| |
| if (acknowledged_bitrate_.has_value() && |
| config_->append_acknowledged_rate_candidate) { |
| bandwidths.push_back(*acknowledged_bitrate_); |
| } |
| |
| if (IsValid(delay_based_estimate) && |
| config_->append_delay_based_estimate_candidate) { |
| bandwidths.push_back(delay_based_estimate); |
| } |
| |
| const DataRate candidate_bandwidth_upper_bound = |
| GetCandidateBandwidthUpperBound(); |
| |
| std::vector<ChannelParameters> candidates; |
| candidates.resize(bandwidths.size()); |
| for (size_t i = 0; i < bandwidths.size(); ++i) { |
| ChannelParameters candidate = current_estimate_; |
| candidate.loss_limited_bandwidth = std::min( |
| bandwidths[i], std::max(current_estimate_.loss_limited_bandwidth, |
| candidate_bandwidth_upper_bound)); |
| candidate.inherent_loss = GetFeasibleInherentLoss(candidate); |
| candidates[i] = candidate; |
| } |
| return candidates; |
| } |
| |
| LossBasedBweV2::Derivatives LossBasedBweV2::GetDerivatives( |
| const ChannelParameters& channel_parameters) const { |
| Derivatives derivatives; |
| |
| for (const Observation& observation : observations_) { |
| if (!observation.IsInitialized()) { |
| continue; |
| } |
| |
| double loss_probability = GetLossProbability( |
| channel_parameters.inherent_loss, |
| channel_parameters.loss_limited_bandwidth, observation.sending_rate); |
| |
| double temporal_weight = |
| temporal_weights_[(num_observations_ - 1) - observation.id]; |
| |
| derivatives.first += |
| temporal_weight * |
| ((observation.num_lost_packets / loss_probability) - |
| (observation.num_received_packets / (1.0 - loss_probability))); |
| derivatives.second -= |
| temporal_weight * |
| ((observation.num_lost_packets / std::pow(loss_probability, 2)) + |
| (observation.num_received_packets / |
| std::pow(1.0 - loss_probability, 2))); |
| } |
| |
| if (derivatives.second >= 0.0) { |
| RTC_LOG(LS_ERROR) << "The second derivative is mathematically guaranteed " |
| "to be negative but is " |
| << derivatives.second << "."; |
| derivatives.second = -1.0e-6; |
| } |
| |
| return derivatives; |
| } |
| |
| double LossBasedBweV2::GetFeasibleInherentLoss( |
| const ChannelParameters& channel_parameters) const { |
| return std::min( |
| std::max(channel_parameters.inherent_loss, |
| config_->inherent_loss_lower_bound), |
| GetInherentLossUpperBound(channel_parameters.loss_limited_bandwidth)); |
| } |
| |
| double LossBasedBweV2::GetInherentLossUpperBound(DataRate bandwidth) const { |
| if (bandwidth.IsZero()) { |
| return 1.0; |
| } |
| |
| double inherent_loss_upper_bound = |
| config_->inherent_loss_upper_bound_offset + |
| config_->inherent_loss_upper_bound_bandwidth_balance / bandwidth; |
| return std::min(inherent_loss_upper_bound, 1.0); |
| } |
| |
| double LossBasedBweV2::GetHighBandwidthBias(DataRate bandwidth) const { |
| if (IsValid(bandwidth)) { |
| return config_->higher_bandwidth_bias_factor * bandwidth.kbps() + |
| config_->higher_log_bandwidth_bias_factor * |
| std::log(1.0 + bandwidth.kbps()); |
| } |
| return 0.0; |
| } |
| |
| double LossBasedBweV2::GetObjective( |
| const ChannelParameters& channel_parameters) const { |
| double objective = 0.0; |
| |
| const double high_bandwidth_bias = |
| GetHighBandwidthBias(channel_parameters.loss_limited_bandwidth); |
| |
| for (const Observation& observation : observations_) { |
| if (!observation.IsInitialized()) { |
| continue; |
| } |
| |
| double loss_probability = GetLossProbability( |
| channel_parameters.inherent_loss, |
| channel_parameters.loss_limited_bandwidth, observation.sending_rate); |
| |
| double temporal_weight = |
| temporal_weights_[(num_observations_ - 1) - observation.id]; |
| |
| objective += |
| temporal_weight * |
| ((observation.num_lost_packets * std::log(loss_probability)) + |
| (observation.num_received_packets * std::log(1.0 - loss_probability))); |
| objective += |
| temporal_weight * high_bandwidth_bias * observation.num_packets; |
| } |
| |
| return objective; |
| } |
| |
| DataRate LossBasedBweV2::GetSendingRate( |
| DataRate instantaneous_sending_rate) const { |
| if (num_observations_ <= 0) { |
| return instantaneous_sending_rate; |
| } |
| |
| const int most_recent_observation_idx = |
| (num_observations_ - 1) % config_->observation_window_size; |
| const Observation& most_recent_observation = |
| observations_[most_recent_observation_idx]; |
| DataRate sending_rate_previous_observation = |
| most_recent_observation.sending_rate; |
| |
| return config_->sending_rate_smoothing_factor * |
| sending_rate_previous_observation + |
| (1.0 - config_->sending_rate_smoothing_factor) * |
| instantaneous_sending_rate; |
| } |
| |
| DataRate LossBasedBweV2::GetInstantUpperBound() const { |
| return cached_instant_upper_bound_.value_or(DataRate::PlusInfinity()); |
| } |
| |
| void LossBasedBweV2::CalculateInstantUpperBound() { |
| DataRate instant_limit = DataRate::PlusInfinity(); |
| const double average_reported_loss_ratio = GetAverageReportedLossRatio(); |
| if (average_reported_loss_ratio > config_->instant_upper_bound_loss_offset) { |
| instant_limit = config_->instant_upper_bound_bandwidth_balance / |
| (average_reported_loss_ratio - |
| config_->instant_upper_bound_loss_offset); |
| } |
| cached_instant_upper_bound_ = instant_limit; |
| } |
| |
| void LossBasedBweV2::CalculateTemporalWeights() { |
| for (int i = 0; i < config_->observation_window_size; ++i) { |
| temporal_weights_[i] = std::pow(config_->temporal_weight_factor, i); |
| instant_upper_bound_temporal_weights_[i] = |
| std::pow(config_->instant_upper_bound_temporal_weight_factor, i); |
| } |
| } |
| |
| void LossBasedBweV2::NewtonsMethodUpdate( |
| ChannelParameters& channel_parameters) const { |
| if (num_observations_ <= 0) { |
| return; |
| } |
| |
| for (int i = 0; i < config_->newton_iterations; ++i) { |
| const Derivatives derivatives = GetDerivatives(channel_parameters); |
| channel_parameters.inherent_loss -= |
| config_->newton_step_size * derivatives.first / derivatives.second; |
| channel_parameters.inherent_loss = |
| GetFeasibleInherentLoss(channel_parameters); |
| } |
| } |
| |
| bool LossBasedBweV2::PushBackObservation( |
| rtc::ArrayView<const PacketResult> packet_results) { |
| if (packet_results.empty()) { |
| return false; |
| } |
| |
| PacketResultsSummary packet_results_summary = |
| GetPacketResultsSummary(packet_results); |
| |
| partial_observation_.num_packets += packet_results_summary.num_packets; |
| partial_observation_.num_lost_packets += |
| packet_results_summary.num_lost_packets; |
| partial_observation_.size += packet_results_summary.total_size; |
| |
| // This is the first packet report we have received. |
| if (!IsValid(last_send_time_most_recent_observation_)) { |
| last_send_time_most_recent_observation_ = |
| packet_results_summary.first_send_time; |
| } |
| |
| const Timestamp last_send_time = packet_results_summary.last_send_time; |
| const TimeDelta observation_duration = |
| last_send_time - last_send_time_most_recent_observation_; |
| |
| // Too small to be meaningful. |
| if (observation_duration < config_->observation_duration_lower_bound) { |
| return false; |
| } |
| |
| last_send_time_most_recent_observation_ = last_send_time; |
| |
| Observation observation; |
| observation.num_packets = partial_observation_.num_packets; |
| observation.num_lost_packets = partial_observation_.num_lost_packets; |
| observation.num_received_packets = |
| observation.num_packets - observation.num_lost_packets; |
| observation.sending_rate = |
| GetSendingRate(partial_observation_.size / observation_duration); |
| observation.id = num_observations_++; |
| observations_[observation.id % config_->observation_window_size] = |
| observation; |
| |
| partial_observation_ = PartialObservation(); |
| |
| CalculateInstantUpperBound(); |
| return true; |
| } |
| |
| } // namespace webrtc |
