Signal-Calling-Service VS glommio

I am npt sure if this is related but Signal built Signal Calling Service and according to them it worked great.

I was curious and looked through the code of Galene briefly and found the following, which may answer your question. For context, I am familiar with the Jitsi code and have written my own calling server (and written about it: https://signal.org/blog/how-to-build-encrypted-group-calls/).

Galene appears to be less mature than Jitsi. For example, it uses REMB feedback messages from the client to calculate allowable bitrates rather than calculating the bitrates itself (as Jitsi and Signal's SFU do). Worse, it appears that what it does with that information is erroneous. I could be wrong, but it looks like the bitrate allocation code (see https://github.com/jech/galene/blob/e8fbfcb9ba532f733405b1c5...) only allocates the bitrate for one of the video streams, not all of them. Perhaps the author did not realize that there is one REMB sent back for all the video streams by WebRTC rather than one per stream (see, for example, here: https://source.chromium.org/chromium/chromium/src/+/main:thi...). Further, I find the spatial layer switching code to be strange. For examples, it doesn't go down a layer unless it's 150% over the estimated allowable bitrate, which gives a lot of opportunity for inducing latency.

In short, I think Galene has a ways to go before it works as well as Jitsi (Videobridge), and thus Pyrite group calls are unlikely to work as well as Jitsi group calls (for 1:1 calls, I don't know; I didn't look into that).

Oh, and just a reminder, the SFU we use for Signal group calls is also open source: https://github.com/signalapp/Signal-Calling-Service.

And yeah, it uses Signal-Calling-Service written on Rust.

That's a well written article covering the basics of simulcast.

If you're interested in seeing an implementation of an SFU doing simulcast forwarding written in Rust, we (at Signal) recently open sourced our SFU:

https://github.com/signalapp/Signal-Calling-Service/blob/mai...

I used glommio as the async executor (instead of something like tokio), and it is wonderful. For people wondering whether it's "good enough" or to use C++ and seastar (as I have thought about a lot before starting this project), take the leap of faith, it's fast - both in terms of run time and to code.

My understanding is you always need a runtime, somethings needs to drive the async flow. But there are others on the market, just not without the.. market domination... of tokio.

https://github.com/smol-rs/smol looks promising simply for being minimal

https://github.com/bytedance/monoio looks potentially easier to work with than tokio

https://github.com/DataDog/glommio is built around linux io_uring and seems somewhat promising for performance reasons.

I haven't played with any of these yet, because Tokio is unfortunately the path of least resistance. And a bit viral in how it's infected tings.

I think you missed one which is based on io_uring [1].

In my benchmarks with a slightly tweaked version it was 2x faster than Nginx and and 30x faster than Python's SimpleHttpServer.

[1] https://github.com/DataDog/glommio/blob/master/examples/hype...

b) It's proven now e.g Seastar, Glommio that the fastest way to run a multi-threaded application is to have one instance with one thread pinned per CPU core. Then to have fibers/lightweight threads on top handling all of the asynchronous code. Your approach of lots of instances is the slowest so there will be a ton of unnecessary thread context-switching.

I assume Tokio itself, see e.g monoio or glommio, but also Seastar for C++.

https://github.com/DataDog/glommio Rust thread per core library.

> Few of us have really figured out io_uring. But that doesn't mean it is slower.

seastar.io is a high level framework that I believe has "figured out" io_uring, with additional caveats the framework imposes (which is honestly freeing).

Additionally the rust equivalent: https://github.com/DataDog/glommio

This use case is perfect for https://github.com/DataDog/glommio which is a thread-per-core runtime that is appropriate for latency sensitive code.

It's worth mentioning: Under "Async Executors", for "io_uring" there is only "Glommio"

I recently found out that ByteDance has a competitor library which supposedly has better performance:

https://github.com/bytedance/monoio

https://github.com/DataDog/glommio/issues/554

FYI, Datadog has a Rust library for scheduling things to run thread-per-core with io_uring

It'd be really useful for DB use cases:

https://github.com/DataDog/glommio