Seeing Patterns in Random Data
What we are after is very consistent data connections for our customers and clients. Below is one way to help quantify that your Wireless LAN is giving your clients consistent results. I know not everyone enjoys statistics… but sometimes with just a little massaging of data, in this case sorting the data first, will help allow you to see patterns–information–in your data. Rather than just take a single sample of data throughput, take a bunch. In this case I took 25 samples – the more the better. Now you can see more than a single snapshot in time – but a set of datapoints that we can learn much more from than a single point.
When looking at collected data, sometimes it seems to be quite random in nature. Looking at this random data, folks can make mistakes in analysis. One method we use to help ‘clean up’ this random data is to first sort the collected data from high to low, and graph according to percentage. This allows us to see graphically the differences between data sets.
As an example, I’ve put together the following sample data sets. Each has the exact same Maximum, Minimum and Average… but obviously, much different results. This is the value of this sorting method, it allows one to quickly see differences in data.
| Maximum | 20 |
| Minimum | 5 |
| Average | 11.36 |
| Datapoints | 25 |
Seemingly Random Data
The first is a graph showing the two sets of data, fairly random looking. Both look like they are quite similar in nature, both inconsistent, and with a fairly same average.
Consistent vs Inconsistent Data
But when you take this same information and sort it first, you can see distinct differences in the resulting graphs. One set of data is much more consistent than the other. Even though they both have the same averages.
We’d like to see very flat lines, showing customer experiences to be fairly consistent across the board. The higher the lines the higher the client’s throughput results.
A line with it’s curve toward the bottom left represents a fairly low consistent result. A diagonal line represents high variability – more inconsistency. A line with the curve in the upper right represents consistently higher results.
Another way to use these ‘sorted’ graphs is to look at the 50% line – this represents the ‘average’ someone would achieve. The 80% line on the bottom represents that 80% of all collected data meets or exceeds this number.
This is a good telltale sign for following the 80/20 rule. Don’t waste too much time and money trying to fix the last 20% – put the bulk of your resources towards getting the 80% to be as consistent (flat) as possible.
Words Have Meanings?
Many decades ago I lived in Taiwan for a couple of years and learned Mandarin Chinese. Of all the tens of thousands of possible Chinese characters, there are only some 400 or so different sounds in the language. So many of the same characters (words) end up having the exact same sound. To counteract this obvious chance for confusion, sometimes Chinese people write out an imaginary copy of the character in question on the palm of their hand. A bit awkward, but it helps to convey which character goes with which sound.
In the English language, we too have difficulties at times with words having the same sound, but entirely different meanings. Some even represent a noun, and a verb with the exact same sound. For example, take the word Shift.
- Shift – to change gears on a car
- Shift – a type of woman’s apparel
- Shift – a time period for work
- Shift – what a Defense does in American Football
- Shift – an improvised knife used as a weapon
Thus we need context around the word to help us determine which version we are referring to.
As another example – the word Braces:
“You wouldn’t want to confuse the Braces holding up Larry King’s pants, with the Braces straightening his teeth, with the guest who Braces for the next question.”
In our world of Wireless LANs we too have to be careful in the use of various terms and words that can have different possible meanings.
We banter about the term ‘Spectrum Analyzer’ but which version might we be referring to:
- A $30,000 Spectrum Analyzer used in electronics labs?
- A $4,000 Cognio Spectrum Analyzer with custom ASICs?
- A $2,000 AirMagnet Spectrum Analyzer with software to share with WiFi NIC data?
- A $400 MetaGeek Spectrum Analyzer?
- An Atheros chipset with WiFi mode turned off and listening as a Spectrum Analyzer?
- Or finally what Xirrus calls a Spectrum Analyzer – but is just WiFi data in tabular format?
All are referred to as a Spectrum Analyzer – but they all have far different resolutions, and capabilities. Not that the most expensive is best – you’ll need to use the one that can show you the raw (non-Modulated) RF at the resolution you need to solve your current problem.
Set SoapBox = ON
Xirrus – just calling something a Spectrum Analyzer doesn’t make it one. No more than calling me a Marathon Runner makes me one. (I have ‘run’ (managed) the electronic timers at a Marathon – that doesn’t mean I actually competed) If your device cannot ‘see’ raw non-modulated RF – don’t call it something it isn’t. It might fool your customers – but not anyone who actually knows what a Spectrum Analyzer is!
Set SoapBox = OFF
Other words we use in the pursuit of our Wireless LAN systems that can be confusing include the word Interference.
We have:
- Raw RF Interference – non-802.11 modulated
- Co-Channel Interference – 802.11 packets on the same frequency
- Adjacent Channel Interference – 802.11 packets on nearby frequencies
- Interference because AP’s and Clients are sharing the same frequency with all neighboring devices on the same channel. (Like a hub has interference from all connected devices)
Each of these effects on our data throughput differently, and each need different tools to help troubleshoot and solve the “Interference”.
Or how about the simple term Noise that gets thrown around all the time. Which version of Noise are you referring to:
- Thermal Noise?
- Non-802.11 Modulated RF signals?
- 801.11 RF on the same channel?
- 802.11 RF on nearby channels?
- Ambient RF noise floor?
- Broken Packets on the same frequency?
Which of these above is what you are thinking of for the ‘N’ in SNR? Which version of “Noise” is used in your Wi-Fi NIC?
Spectrum Analyzers can tell some of these, a Wi-Fi NIC that is in promiscuous mode can see others. Knowing when to use which tool is very important.
In conclusion – remember just like the words Shift and Braces – we need to be very precise in the use of confusing Wireless LAN terms. It will help clear up any confusion if you can be very precise when communicating terms like Spectrum Analyzer, Interference, and Noise.
