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

Feb 05, 20184 mins
Artificial IntelligenceNetworkingWi-Fi

AI replaces manual WiFi management tasks with automated intelligence and provides deep insight that helps identify and fix problems faster than ever before.

Wi-Fi tools
Credit: Thinkstock

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:

For six months, a Fortune 100 company has been plagued with an intermittent device connectivity issue. Occasionally, the scanners don’t scan. They have deployed onsite IT admins, network engineers, instrumented the warehouse with sniffers on all channels, just to catch the problem while it happens. Six months go by. The problem persisted all over the world in warehouse around the company. Frustration built among the business users, and it was costing the company millions in lost productivity. So how can modern Wi-Fi solve this?

Thanks to artificial intelligence (AI), the solution to the problem described above was discovered in just minutes – the mean time to innocence dropping from months to minutes once they replaced their legacy controller Wi-Fi with an AI-driven network. It’s all thanks to the modern technology that lets us collect huge amounts of data from every mobile client and move it to the cloud where events are correlated using machine learning. Then anomalies can be detected in real-time, and recommendations are given (or performed automatically) to correct any issues before users even know they exist. In this particular case, the AI-driven wireless network got a dynamic packet capture the first time the issue happened. Within 45 minutes of installing the AI-driven cloud wireless, they had a packet capture. And the packet capture doesn’t lie! It proved the problem was never with the “wireless network” – this particular company was setting their roaming request incorrectly. Within three days a solution was discovered, which was then rolled out globally.

IT administrators can also set up service levels to ensure user performance never drops below customized thresholds. For example, the IT department in the scenario above could have set a “roaming” threshold of sub-second for all Wi-Fi users. The minute a roaming threshold was violated, a series of automated events could have been triggered to alert IT of the issue and give them the actionable insight they needed to rapidly resolve it.

AI replaces manual Wi-Fi management tasks with automated intelligence and provides deep insight that helps identify and fix problems faster than ever before.  This is the direction that all IT is going – and Wi-Fi is right there on the front line.


Sudheer Matta brings more than 15 years of wireless and networking industry experience to his role as vice president of Product Management at Mist Systems. He is responsible for successfully leading product strategy for the company, which has built the first wireless platform for the smart device era.

Prior to Mist, Sudheer held leadership roles in product management and sales at Cisco, Juniper Networks and Trapeze Networks. Prior to that, he held engineering roles at Trapeze and Cirrus Logic where he served as lead 802.11 developer and strategist, wrote code and designed wireless networking solutions.

Sudheer has been involved with the IEEE and Wi-Fi Alliance for 10 years. Most recently he chaired the Wi-Fi Alliance Healthcare Task Group and vice-chaired the Wi-Fi Alliance Network Management Task Group. He served as standards lead in roles at Cisco and Trapeze Networks and was recognized as a major contributor in the 802.11k standard amendment. He holds six assigned and two pending patents, including the patent for the widely implemented Band Steering technology.

The opinions expressed in this blog are those of Sudheer Matta and do not necessarily represent those of IDG Communications, Inc., its parent, subsidiary or affiliated companies.