Excellent discussion - and the application area (cross-correlation of sensor network data) is actually quite a bit more popular than one might think! Avalanche/landslide detection, earthquakes, bridge monitoring, industrial settings...
On a tangent, if those cross-correlations are big-ish a frequency domain (FFT) correlation could be more efficient, assuming that hasn't already been tried. This would probably save storage memory as well, though I am not 100% sure. If you could get the sensors to send the FFTs directly that could be even better!
This also has echoes of a previous HN discussion on space filling curves [0], which led to the purchase of this book [1]. I still haven't dug into it yet, but maybe these are useful references for others who are interested.
On a tangent, if those cross-correlations are big-ish a frequency domain (FFT) correlation could be more efficient, assuming that hasn't already been tried. This would probably save storage memory as well, though I am not 100% sure. If you could get the sensors to send the FFTs directly that could be even better!
This also has echoes of a previous HN discussion on space filling curves [0], which led to the purchase of this book [1]. I still haven't dug into it yet, but maybe these are useful references for others who are interested.
[0] https://news.ycombinator.com/item?id=7480857
[1] http://www.amazon.com/Space-Filling-Curves-Introduction-Appl...