- Anatomy of a WebRTC SDP
- AIY Vision Kit Part 1: TensorFlow Computer Vision on a Raspberry Pi Zero
- Guide to WebRTC with Safari in the Wild (Chad Phillips)
- How to Figure Out WebRTC Camera Resolutions
- Computer Vision on the Web with WebRTC and TensorFlow
- An Intro to WebRTC’s NAT/Firewall Problem
- Reeling in Safari on WebRTC – A Closer Look at What’s Supported
webrtcH4cKS: ~ Breaking Point: WebRTC SFU Load Testing (Alex Gouaillard)
If you plan to have multiple participants in your WebRTC calls then you will probably end up using a Selective Forwarding Unit (SFU). Capacity planning for SFU’s can be difficult – there are estimates to be made for where they should be placed, how much bandwidth they will consume, and what kind of servers you need.
To help network architects and WebRTC engineers make some of these decisions, webrtcHacks contributor Dr. Alex Gouaillard and his team at CoSMo Software put together a load test suite to measure load vs. video quality. They published their results for all of the major open source WebRTC SFU’s. This suite based is the Karoshi Interoperability Testing Engine (KITE) Google funded and uses on webrtc.org to show interoperability status. The CoSMo team also developed a machine learning based video quality assessment framework optimized for real time communications scenarios.