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Nonlinear Neural Nets Smooth Wi-Fi Packets
mindless4210 writes "Smart Packets, Inc has developed the Smart WiFi Algorithm, a packet sizing technology which can predict the near future of network conditions based on the recent past. The development was originally started to enable smooth real-time data delivery for applications such as streaming video, but when tested on 802.11b networks it was shown to increase data throughput by 100%. The technology can be applied at the application level, the operating system level, or at the firmware level."
the technology can be executed at any of those level to be effective, not all 3 at once. So that means linux could get support for it at the kernel level... someone could write an application for windows, and palms could use an updated firmware and all 3 would effectively take advantage of the algo.
Umm... it isn't so simple. You are missing the basic idea of a layered architecture. This is actually really cool that it can be implemented at any layer. Sometimes there are things that can't be done at the application layer because of the constraints created by the layers below it. For instance, it is pretty worthless to do routing at the application layer if you are using IP, because it is already taken care of at the network layer.
So to say that it is all just "software" misses the fact that there is a significant difference between how these peices of software work. It is really cool that this can be done at the application layer, because it will allow applications to be developed to take advantage of it with out even changing the drivers for your wi-fi card.
Heres a graph that I ripped out of some lecture notes. It shows how much of a problem congestion is on 802.11b networks.
.035 Mbps per host.
http://web.ics.purdue.edu/~dphillip/802.11b.gif
For a little explaination, where it says "Node 50" or "Node 100" that means that there are 50 or 100 computers on the wireless network. And the throughput numbers are for the whole network, not per host. So when 100 nodes are getting 3.5 Mbps that's
Thanks to professor Park
When I see the headline: "Nonlinear Neural Nets Smooth Wi-Fi Packets" and I only understand the words nets, smooth and packets...and none of them in relation to each other
;-)
Simple 'nuff, really...
Neural net - An arrangement of "dumb" processing nodes in a style mimicing that which the greybacks of AI (such as Minsky and Turing et al) once believed real biological neurons used. Basically, each node has a set of inputs and outputs. It sums all its inputs (each with a custom weight, the part of the algorithm you actually train), performs some very simple operation (such as hyperbolic tangent) called the "transfer function" on that sum, then sets all of its outputs to that value (which other neurons in turn use as their inputs).
Nonlinear - This refers to the shape of the transfer function. A linear neural net can, at best, perform linear regression. You don't need a neural net to do that well (in fact, you can do it a LOT faster with just a single matrix inversion). So calling it "nonlinear" practically counts as redundant in any modern context.
Smooth - A common signal processing task involves taking a noisy signal, and cleaning it up.
Wi-Fi - An example of a fairly noisy signal that would benefit greatly from better prediction of the signal dynamics, and from better ability to clean the signal (those actually go together, believe it or not - In order to "clean" the signal without degrading it, you need to know roughly what it "should" look like).
Packets - The unit in which "crisps" come. Without these, you can't use a Pringles can to boost the gain on your antenna to near-illegal values.
There, all make sense now?