@(webrtc)[webrtc, congestion control]

Webrtc delay-base-bwe代码分析(6): 整体分析

当收到RTP数据包时，会触发RemoteBitrateEstimatorSingleStream::IncomingPacket函数进行处理。
这里面使用到了之前几篇文章分析的模块，各自进行各自的处理。

void RemoteBitrateEstimatorSingleStream::IncomingPacket(    int64_t arrival_time_ms,    size_t payload_size,    const RTPHeader& header) {  uint32_t ssrc = header.ssrc;  uint32_t rtp_timestamp = header.timestamp +      header.extension.transmissionTimeOffset;  int64_t now_ms = clock_->TimeInMilliseconds();  CriticalSectionScoped cs(crit_sect_.get());  SsrcOveruseEstimatorMap::iterator it = overuse_detectors_.find(ssrc);  // 根据SSRC查找对应的检测器  if (it == overuse_detectors_.end()) {    // This is a new SSRC. Adding to map.    // TODO(holmer): If the channel changes SSRC the old SSRC will still be    // around in this map until the channel is deleted. This is OK since the    // callback will no longer be called for the old SSRC. This will be    // automatically cleaned up when we have one RemoteBitrateEstimator per REMB    // group.    std::pair<SsrcOveruseEstimatorMap::iterator, bool> insert_result =        overuse_detectors_.insert(std::make_pair(            ssrc, new Detector(now_ms, OverUseDetectorOptions(), true)));    it = insert_result.first;  }  Detector* estimator = it->second;  estimator->last_packet_time_ms = now_ms;  // Check if incoming bitrate estimate is valid, and if it needs to be reset.  // 会先以当前时间为基准，从历史的传输数据中尝试获取未更新当前时间的旧码率值。  rtc::Optional<uint32_t> incoming_bitrate = incoming_bitrate_.Rate(now_ms);  if (incoming_bitrate) {    last_valid_incoming_bitrate_ = *incoming_bitrate;  } else if (last_valid_incoming_bitrate_ > 0) {    // Incoming bitrate had a previous valid value, but now not enough data    // point are left within the current window. Reset incoming bitrate    // estimator so that the window size will only contain new data points.    incoming_bitrate_.Reset();    last_valid_incoming_bitrate_ = 0;  }  // 在历史传输数据中更新当前数据。  incoming_bitrate_.Update(payload_size, now_ms);  const BandwidthUsage prior_state = estimator->detector.State();  uint32_t timestamp_delta = 0;  int64_t time_delta = 0;  int size_delta = 0;  // 到达时间统计已经有足够样本构成一个新的group时，  if (estimator->inter_arrival.ComputeDeltas(          rtp_timestamp, arrival_time_ms, now_ms, payload_size,          &timestamp_delta, &time_delta, &size_delta)) {    double timestamp_delta_ms = timestamp_delta * kTimestampToMs;    // 根据到达时间间隔，更新卡尔曼滤波器    estimator->estimator.Update(time_delta, timestamp_delta_ms, size_delta,                                estimator->detector.State());    // 根据卡尔曼滤波器校准后的值，更新当前链路使用状态。    estimator->detector.Detect(estimator->estimator.offset(),                               timestamp_delta_ms,                               estimator->estimator.num_of_deltas(), now_ms);  }  // 当处于连续过载状态时候需要立刻对码率进行更新，  // 如果是其他状态，会由定时器在Process函数中更新对应状态。  // UpdateEstimate会对状态机AimdRateControl进行处理。  if (estimator->detector.State() == kBwOverusing) {    rtc::Optional<uint32_t> incoming_bitrate_bps =        incoming_bitrate_.Rate(now_ms);    if (incoming_bitrate_bps &&        (prior_state != kBwOverusing ||         remote_rate_->TimeToReduceFurther(now_ms, *incoming_bitrate_bps))) {      // The first overuse should immediately trigger a new estimate.      // We also have to update the estimate immediately if we are overusing      // and the target bitrate is too high compared to what we are receiving.      UpdateEstimate(now_ms);    }  }}

简单流程图：