The article doesn't directly mention network partitions and split-brain syndrome. Luckily there is Aphyr's Jepsen series [1] with both theory and practice.
The algorithm is called "Jump". A quick search on GitHub revealed three projects that implement it and they are all written in Go: https://github.com/benbjohnson/jmphash
And not just that hardware is harder but also the IoT market is estimated at $19 trillion [1] creating a gold rush of sorts.
But yes, there is no shortage of IoT platforms (xively, dweet, nitrogen, data.sparkfun, ...) and I'm partly in involved as well. What I found interesting about the MS program is that recently they were giving away boards for you to try. So it seems they are in a position to provide the hardware and the platform.
Looks great, I've been looking for a solution like this. What would be really cool is to be able to query public data streams and combine them in way similar to Yahoo Pipes.
I suspect people will also want to run aggregations/rollups of their data and that's something we enable in Streametry [1] in addition to other analytics. I might try to build a a bridge to Sparkfun.
Lack of hover effects caught my attention as well. Additionally for time series data range selectors come in handy. Dygraphs [1], NVD3 [2] and Highcharts all have them.
[1] http://aphyr.com/tags/Jepsen