Earlier this week I was a guest on TechRepublic’s “The Upside” podcast where I talked to Chris Duckett about the Mass Mobile Experiment – an open source collaboration platform I developed with Simon Raik-Allen from MYOB. We recently showcased the technology at Tech Ed Australia.
“One of the most interesting talks at this year’s Australian TechEd event was the Mass Mobile Experiment. The platform’s Pong implementation was used to entertain attendees before the conference’s keynote.”
We chat about the inspiration for project – Loren Carpenter’s crowd swarming pong experiment from 1991 and we geek out about TypeScript and node.js
Here’s a link to the podcast
I’ve been working on a pretty cool side project that I presented at Tech Ed Australia 2012 – “The Mass Mobile Experiment!”
It’s a generic collaboration framework that enables lots of people (say at a conference) to enjoy a shared experience in real time using their mobile phone, tablet or other internet device. At my Tech Ed session I had over100 people playing a single game of pong on the big screen using their mobile phones to control the paddles in real time! The platform is built using node.js, websockets (socket.io) and it supports a plug-in architecture enabling other games / experiences to plug in pretty easily. So far I’ve got a multi-player quiz game, pong, a political worm and an interactive presentation.
Conceptual Architecture – MME ( Mass Mobile Experiment)
- Client ( mobile phone) sends data to server over long running websocket
- Server (node.js) aggregates the data and sends to the playfield over websockets
- Playfield (browser on a big screen) runs the game loop and process the aggregated data from the server.
- Control Panel allows you to change games and throttle the client and server
Bench marking on Windows Azure
In order to load test the platform I built yet another game! This time I got 200 people in the office to “play the game”. It involved leaving a web page open for 20 minutes while I stepped up the number of websocket connections on each browser and started to send data to the server.
- The client connects to the server over websockets and sends typical game data on a timer
- The server collects interesting metrics such as requests per second and CPU and sends this to the playfield
- The playfield ( load test app) listens for data over another websocket and plots the data in real time
- Node.js server running on a medium size worker role on Window Azure, 3.5 GB RAM, Allocated Bandwidth 200 (Mbps).
- 2000 concurrent WebSockets ( multiplexing over 200 different laptops in the office)
- Requests per second 8500
- Memory Usage on Azure 76%
- Message send frequency from client – 4 messages per second
Check out this screenshot from the azure management portal – I managed to push the CPU to a 89% at 11:40 when the system ramped up to 2000 concurrent users!
- Node.js running on an azure worker role scales really really nicely. In my case a medium sized VM scaled to 2000 concurrent web sockets processing 8000 requests per second. Not a single message got lost between the browser and the server even when the server was under stress!
Why you should distrust this post !
- The measurements were taken using node.js v0.8.9, socket.io v 9.0, these technologies are evolving rapidly.
- For the mass mobile experiment the node server is pretty simplistic, it aggregates data and sends it to the playfield. This may not represent what your application is doing.
All of the results along with all of the source code is open sourced here on GitHub
May the source be with you !