Abstract: A method includes, at a media bridge configured to distribute a plurality of media streams among a plurality of client devices connected to the media bridge over a network, receiving the plurality of media streams from the plurality of client devices via the media bridge. The media bridge connects the plurality of client devices. The method further includes assigning a pair of names for each of the plurality of media streams. The pair of names include a contribution name and a distribution name. The method further includes presenting a first list to the plurality of client devices. The first list including a plurality of the distribution names for the plurality of media streams received from the plurality of client devices. The method further includes providing an indication of a current active speaker within the plurality of media streams via a signaling process.

Abstract: In one example, a location of a potential bottleneck of network traffic in a network is identified. Based on the location of the potential bottleneck, a first QoE inference model is selected from a plurality of respective QoE inference models. The respective QoE inference models are each trained to infer a respective QoE of the network traffic based on one or more respective network traffic metrics generated by monitoring the network traffic at a respective location in the network. One or more first network traffic metrics of the one or more respective network traffic metrics are generated by monitoring the network traffic at a first respective location. The one or more first network traffic metrics are provided to the first QoE inference model to infer a first respective QoE.

Abstract: In one embodiment, a device determines a first difference between current path measurements and prior path measurements. The device determines a second difference between current predictions and prior predictions made by a prediction model based on path measurements. The device computes, based on the first difference and the second difference, an interest metric for the current path measurements. The device sends at least a portion of the current path measurements for input to the prediction model, when the interest metric exceeds a predefined threshold.

Abstract: In one example, a location of a potential bottleneck of network traffic in a network is identified. Based on the location of the potential bottleneck, a first QoE inference model is selected from a plurality of respective QoE inference models. The respective QoE inference models are each trained to infer a respective QoE of the network traffic based on one or more respective network traffic metrics generated by monitoring the network traffic at a respective location in the network. One or more first network traffic metrics of the one or more respective network traffic metrics are generated by monitoring the network traffic at a first respective location. The one or more first network traffic metrics are provided to the first QoE inference model to infer a first respective QoE.

Abstract: A method includes, at a media bridge configured to distribute a plurality of media streams among a plurality of client devices connected to the media bridge over a network, receiving the plurality of media streams from the plurality of client devices via the media bridge. The media bridge connects the plurality of client devices. The method further includes assigning a pair of names for each of the plurality of media streams. The pair of names include a contribution name and a distribution name. The method further includes presenting a first list to the plurality of client devices. The first list including a plurality of the distribution names for the plurality of media streams received from the plurality of client devices. The method further includes providing an indication of a current active speaker within the plurality of media streams via a signaling process.

Abstract: A method includes, at a media bridge configured to distribute a plurality of media streams among a plurality of client devices connected to the media bridge over a network during a real-time communication (RTC) instance, receiving a plurality of quality of experience (QoE) preferences from the plurality of client devices via the media bridge, the plurality of QoE preferences being transmitted as a real-time transport protocol (RTP) control protocol (RTCP) extension header of a transmitted data packet. The method also includes receiving a plurality of QoE metrics at the media bridge, and in response to a determination that a degradation in network conditions of the network has occurred, downgrading at least one of the plurality of media streams based on the plurality of QoE preferences.

Abstract: A method includes, at a media bridge configured to distribute a plurality of media streams among a plurality of client devices connected to the media bridge over a network during a real-time communication (RTC) instance, receiving a plurality of quality of experience (QoE) preferences from the plurality of client devices via the media bridge, the plurality of QoE preferences being transmitted as a real-time transport protocol (RTP) control protocol (RTCP) extension header of a transmitted data packet. The method also includes receiving a plurality of QoE metrics at the media bridge, and in response to a determination that a degradation in network conditions of the network has occurred, downgrading at least one of the plurality of media streams based on the plurality of QoE preferences.