Waku is our fork of Whisper where we address the shortcomings of Whisper in an iterative manner. We've seen a in [previous post](https://vac.dev/fixing-whisper-with-waku) that Whisper doesn't scale, and why. In this post we'll talk about what the current state of Waku is, how much users it can support, and briefly on future plans.
We released [Waku spec v0.3](https://specs.vac.dev/waku/waku.html) this week! You can see a full changelog [here](https://specs.vac.dev/waku/waku.html#changelog).
The main change from 0.2 is changing the handshake to be more flexible by specifying options as an association list. The driving force for this was making sure we could immediately communicate a list of topics a client is interested in in an unambiguous way. This will also give us more flexibility going forward in terms of capabilities and requirements we want to communicate between peers. We also added a recommendation for DNS based discovery and an upgradability/compatibility policy.
Additionally, we've cut the spec up into three components. This is in-line with our goal of making Vac as modular as possible. The components are:
There are currently two clients that implement Waku, these are [Nimbus](https://github.com/status-im/nimbus/tree/master/waku) in Nim and [status-go](https://github.com/status-im/status-go) in Go.
In terms of end user applications, work is currently in progress to integrate it into the [Status core app](https://github.com/status-im/status-react/pull/9949) using the statusg-go client. It is expected to be released in their upcoming 1.1 release (see [Status app roadmap](https://trello.com/b/DkxQd1ww/status-app-roadmap)).
We've got a [simulation](https://github.com/status-im/nimbus/tree/master/waku#testing-waku-protocol) in the Nimbus client that verifies - or rather, fails to falsify - the scalability model described in an [earlier post](https://vac.dev/fixing-whisper-with-waku). More on this below.
This is our current understanding of how many users a network running the Waku protocol can support. Specifically in the context of the Status chat app, since that's the most immediate consumer of Waku. It should generalize fairly well to most deployments.
We've already seen the first bottleneck being discussed in the initial post. Dean wrote a post on [DNS based discovery](https://vac.dev/dns-based-discovery) which explains how we will address the likely second bottleneck. More on the third one in future posts.
For more details on these bottlenecks, uncertainty and mitigations, see [Scalability estimate: How many users can Waku and the Status app support?](https://discuss.status.im/t/scalability-estimate-how-many-users-can-waku-and-the-status-app-support/1514).
We have two network topologies, Star and full mesh, with 6 randomly connected nodes, one traditional light node with bloom filter (Whisper style) and one Waku light node.
One of the full nodes sends 1 envelope over 1 of the 100 topics that the two light nodes subscribe to. After that, it sends 10000 envelopes over random topics.
For light node, bloom filter is set to almost 10% false positive (bloom filter: n=100, k=3, m=512). It shows the number of valid and invalid envelopes received for the different nodes.
- Waku light node gets ~1000x less envelopes than Whisper light node
- Full mesh results in a lot more duplicate messages, expect for Waku light node
Run the simulation yourself [here](https://github.com/status-im/nimbus/tree/master/waku#testing-waku-protocol). The parameters are configurable, and it is integrated with Prometheus and Grafana.
When it comes to the third bottleneck mentioned aboe, a likely candidate for addressing this
is using Kademlia routing. This is similar to what is done in PSS, but there are a few different ways of doing it (classical vs forwarding Kademlia, etc). We are in the early stages of experimenting with this over libp2p in
[nim-libp2p](https://github.com/status-im/nim-libp2p). More on this in a future post!