According to a recent NPD study, 57% of consumers who own web-connected TV's watch movies and videos on Netflix, while 47% access YouTube. While this is a victory for Netflix over the perennial leader in online video consumption, it really comes as no surprise.
Basically, 63 years ago someone calculated the maximum speed at which data could be transmitted wirelessly, and a number of times since then that person's calculation has been mathematically proven to be accurate. Now, OnLive founder Steve Perlman claims his company has found a way to shatter that cap, while at the same time providing a way to make transfer limits on cell phone plans obsolete.
The Shannon–Hartley law is a hard limit for any data channel that goes beyond just a mathematical truth. It's at the heart of what an information transfer is. It isn't really a hard cap so much as it is a rule about how much information any given channel can possibly carry.
The channel capacity is given by;
S/N is the signal to noise ratio, which tends to be dependent on the hard physics of your transfer technology, be it fibre or wifi. B is the bandwidth (in Hz) of the channel. This means for any given technology the capacity is strongly dependent on the bandwidth available. When you are talking about wireless, Shannon's Law is largely the limit of how much information any given transmitter technology can cram into a slice of air.
What this sounds like is a new way to encrypt and transmit the data, similar to MIMO. That stands for Multiple Input, Multiple Output, compared to single/single for traditional wifi.
MIMO is the technology in 802.11n routers which requires two antennae to work. Roughly what you do is transmit half the signal on one antenna and the other half on the other. You then use multiple antennae at the receiving end to distinguish between the two signals and recover the originals. You need multiple antennae so that you can spatially distinguish different signal paths.
The actual way it works is a little more complex, but a simplified version is easy enough to see. Picture two signals being transmitted from two adjacent antennae propagating outwards. The overlapping signal will depend on the path length from each of the two antennae. If you pick two points within this propagating signal then you can use the two different signals (plus information about the positions of each antennae) to find the original signals.
Thing is, the complex, interference signal obeys Shannon's law. It's more that you have increased the effective bandwidth by adding an extra component to the signal; spacial variation. With two antennae at each end you can double the effective bandwidth by encoding two signals into one spatially evolving signal. More antennae cram in more signals.
This new system is referred to as a distributed-input distributed-output (DIDO). From what I can tell this is a new spacial encryption method that they are claiming is massively more efficient than MIMO systems. Note that in this presentation (~55 min onwards) (which doesn't include any real technical meat, just claims) he says as much. Shannon can't be violated, but you can find ways around it.
Except... some of his claims are just weird. Being able to transmit through solid objects and around the curvature of the earth on any frequency? Right... Also he says their technology only uses a single antenna, so not sure how they would do spacial resolution. Going from the Q&A session it sounds like they are somehow modulating the signal from distributed sources to nullify any particular signal outside of it's target. So the signal is effectively zero except directly around your wifi receiver, at which point it is amplified strongly by multiple sources. I can't think of a way to pull this off and I'm not sure it even makes sense.
Tech blog's kinda dead right now, so I figured I'd just share a solution I just figured out to a specific MySQL problem.
Consider the following table structure:
create table imageonevent ( id int unsigned primary key auto_increment, eventid int unsigned not null, imageid int unsigned not null, displayorder int unsigned not null default 1 )
And suppose we have a bunch of images attached to a bunch of events. Now suppose we want to remove an image from the database. In order to maintain the stability of this table, we would then need to lower by 1 the displayorder value of all images in the same event, with a higher display order than the image holds in that event. So if we have data like this:
and we want to remove picture 3 from the database, we would need to adjust down event5/image7 and event6/image1, but not event6/image2.
It took me a few minutes, but I figured out how to do it in a single query:
update imageonevent ioe left join (select eventid, displayorder from imageonevent where imageid = 3) as so on ioe.eventid = so.eventid set ioe.displayorder = ioe.displayorder - 1 where ioe.displayorder > so.displayorder
So there you go; if this ever comes up for you, you can use this solution.
Sadly I wasn't able to load the site you linked us to properly. I was able to read a little bit of it so the first thing that came to mind was this:
Well, that looks like a rosy future for us all if that becomes more common-place. Wouldn't it be ironic if we were having to patch vulnerabilities in viruses to protect ourselves by protecting them from malware?
I was able to load it properly this time, something happened to the layout (most likely CSS) when I loaded it which caused the browser to make a bit of a mess (I get put off sites very quickly if it doesn't look right to me). Anyway, the problem with that site (and only that site) has gone away and I was able to load it properly this time.
Now that I have been able to read it properly it looks like I was wrong with my initial assessment - the sort of thing that the article refers to makes a lot of sense and I am surprised that this hasn't been discovered sooner.
What do you think? _______________________________________________