Mean time to innocence – using AI to uncover the truth behind perceived WiFi issues


Mean Time to Repair (MTTR) is a common term in IT that represents the average time required to repair a failed component or device. In networking, MTTR is often longer than desired because there are many interdependencies, whereby an issue in one part of the network may cause a problem much farther downstream. Furthermore, a configuration change might appear to create a new issue, when in fact it just exposed something that was there all along but hidden. 

It takes quite a bit of forensics to get to the root cause of a network problem. In the meantime (pun intended), there is plenty of blame to go around. The Wi-Fi network seems to be at the top of the list when the accusations fly – more so than any other section of the network. Why is that?

Maybe it is because Wi-Fi is notoriously flaky. Or maybe it is because Wi-Fi is on the “front line” – i.e. people are cognizant of the Wi-Fi network as it is right there in their face, whereas all the other components that go into a successful network experience are hidden, such as DHCP servers, DNS servers, WAN routers, and mobile devices. Furthermore, connecting to the Wi-Fi network is often the last activity taken before things go wrong, so it is natural to think the Wi-Fi network itself is to blame.

However, the Wi-Fi network is often not the actual source of the problem. The wired network, internet, and devices are equally problematic, for example. To clear Wi-Fi’s name – a term wireless admins call “Mean time to Innocence” – IT departments have to sort through a ton of data to get to the actual root cause.  Often times, this can be a challenging task.  Here’s an example that puts things into perspective:

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