I was asked today about troubleshooting wi-fi issues, we ran through the usual basics:
- Check connectivity by connecting via patch cable to the router directly
- Check the status light indicators
- Remove the WEP/WPA security until you get things working and then secure it up
- Look for other devices in the same area
- Change the name, SSID from the standard out of the box settings
- Try using the wireless card drivers instead of the Windows XP standard configuration
- Try a different make of wireless router, ie. Cisco, Linksys, Netgear, etc.
- and so on...
Also pointed to a useful tool called Netstumbler, which can help you identify available networks.
Looking at changing channels and avoiding the overlapping ones
as explained:
So to answer your question, unless you have a specific reason for changing it, I would suggest you keep your wireless channel configured for the manufacturer's default settings. If, however, you must change it, for the best performance I would suggest trying to use one of the other non-overlapping channels first: Channels one, six, and eleven. Other then interference issues, there really is no other reason or advantage to selecting another channel.
It also reminded me of the insecure.org list of top hacking tools, which has some basic port scanner, etc. utilities. For more commerical tools, eEye digital security have a product called Retina security scanner and Iris network analyser which is a fanastic tool for analysing network traffic.
If you are thinking of securing a wireless network in a corporate environment the Microsoft Technet series, "How Microsoft does IT" has an in-depth article on 'Enterprise Deployment of Secure 802.11 Networks Using Microsoft Windows' and 'Troubleshooting Microsoft Windows XP-based Wireless Networks in the Small Office or Home Office'.
It is interesting to read about how neural networks are being used in the MSN Search engine via Adi Olteans's blog.
Looking further at the Microsoft Research papers by Chris Burges I saw one on Audio Fingerprinting.
You have an incoming stream of audio and you'd like to know what's playing. Our system can identify any one of about 240,000 songs in real time using about 10% CPU on an 833 MHz PC. On 36 hours of noisy test audio, it achieves 0.2% false positives at 4.10-6 false negative rate. Confirmation fingerprints can be used to significantly further improve these error rates, with almost no extra CPU cost. Audio fingerprinting has lots of applications: for example, it can be used to construct audio thumbnails for songs, or find duplicate clips on your PC.
When I first tried Shazam from my mobile phone I was impressed it successfully tagged, Frank Sinatra performing 'Bad, Bad Leroy Brown' and I wondered how the technology worked and could search millions of songs so quickly. All I had to do was play the song into my mobile phone for about 15 seconds and then it txt'd me back about 5 seconds later with the artist and track names!
On the subject of SMS txt'ing check out Google SMS UK.
The Microsoft Research project RARE: Robust Audio Recognition Engine papers discuss a similar technology; including a paper on the feature extraction algorithms used, bitvector matching algorithms for fast lookup and using fingerprints to find choruses in music.
Another cool company which licenced work done by Microsoft Research is Inrix for data aggregation of traffic-related content using Bayesian network technology.
What is a Bayesian Network? Bayesian analysis calculates the likelihood of something happening in the face of some particular piece (or pieces) of evidence. Since, traffic volume cannot be predicted using physical laws, we leverage sophisticated Bayesian analysis to create graphs for specific metropolitan areas that map the relationships among real-time traffic, historical traffic patterns, weather, time of day, events, and many other variables. These maps are examples of a Bayesian network.
Where most traffic services can only determine what traffic is like right now – and only in a limited number of cities that have road sensor networks deployed. What they are doing is literally predicting the future which, in addition to providing real-time and incident information, enables answers to questions never before possible such as how long before the congestion there now clears up? Is this congestion normal or an anomaly? This can then be displayed graphically on mobile devices - One to watch.