GStreamer performance on large pipelines

When using GStreamer for creating media middleware and media infrastructures performance becomes critical for achieving the appropriate scalability without degrading end-user QoE. However, GStreamer does not provide off-the-shelf tools for that objective.

In this talk, we present efforts carried out for improving the performance of the Kurento Media Server during the last year. We present our main principle: “you cannot improve what you cannot measure”. Developing on it, we introduce different techniques for benchmarking large GStreamer pipelines including callgrind, time profiling, gst-meta profiling, chain-profiling, etc.

We present results for different pipeline configurations and topologies. After that, we introduce some evolutions for GStreamer which could be helpful for optimizing performance such as the pervasive use of buffer-lists, the introduction of thread-pools or the appropriate management of queues.

To conclude, we present some preliminary work carried out in the GStreamer community for implementing such optimization and we discuss their advantages and drawbacks.

Miguel París is software engineer and has a Msc in Telematics Systems. He works as researcher in new multimedia systems and is the manager of real-time communication area in Kurento team, where is the responsible of the WebRtcEndpoint. He has participated in the design of Kurento architecture and APIs and in the development of Kurento GStreamer elements. In addition, he has contributed to GStreamer community with some patches and discussions about RTP stack and other stuff.