Friday, November 23, 2007

... or is this more appropriate?



Someone at work (thanks, Rob K.) pointed out how maybe my "Biotrophic Parasitic Computing" idea is similar to the relationship between Remy and Linguini in the movie Ratatouille.

Does that sound more pleasant?

Wednesday, November 14, 2007

Biotrophic parasitism as a computing strategy

Biotrophic parasitism is a form of symbiosis between a parasite and it's host. The parasitic organism doesn't destroy it's host, but co-exists with it.

This presents an interesting strategy for embedded computing, or more precisely, the augmentation of existing embedded computing devices. This has, lately, become a consuming interest of mine. But, before I dive into that, here is something a bit more lurid.

This was the basis for my original line of thought: Parasitic fungi that control the behavior of the host. Unfortunately, this is not symbiotic, as the host is ultimately consumed or destroyed. I don't seek to replicate that type of relationship in my embedded augmentation experiments. But, outside of the grisly demise, it's pretty close to what I am talking about.

Consider this: You want to modify the behavior of your Roomba. You attach a microcontroller that feeds off of the Roomba's power and augments the Roomba's behavior through the "Open" serial interace. That microcontroller can be said to be parasitic. If the microcontroller is small enough (e.g. consumes little power from the host) and is well behaved (e.g. won't cause the Roomba to ignore it's cliff sensors), then it is a Biotrophic Parasite.

There are some microcontrollers (and of greater interest: microcontroller boards) that are well suited to biotrophic parasitism. For example: the Lilypad and this (3 for $10) board from TI, that can be programmed by this $20 development board.

Interestingly, I've been doing something along the lines of parasitic computing at my day job.

As I play with my iRobot Create (and forthcoming Roomba), I hope to exploit this technique further.

I like to call it Biotrophic Parasitic Computing.