Thursday, December 5, 2024

Intel Connectivity Analytics To Speed Up RF Troubleshooting

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Troubleshoot Intel Connectivity Analytics Poor RF Issues Fast.

Employee productivity depends on Intel’s corporate wireless local area network (WLAN). Poor Radio Frequency (RF) conditions might cause users to become more frustrated and lose productivity. It has been discovered that proper access point (AP) placement, the outcome of efficient planning, is the first step towards dependable WLAN service. However, planning alone is insufficient to provide the network stability to want, as the recent white paper, “Optimizing and Troubleshooting Wi-Fi Networks Using Client Analytics,” explains.

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Optimizing and Troubleshooting Wi-Fi Networks Using Client Analytics
Image Credit To Cisco Blogs

Intel IT’s Best Practices for Avoiding Poor RF Issues

A few recommendations for optimal AP location have been established by Intel IT:

  • An AP should be placed every 45 feet.
  • In tiny meeting rooms, place an AP next to each of the four corners.
  • Install one access point (AP) for every eight users in bigger conference rooms.

Although these recommendations don’t always achieve the 99.999% coverage target, to estimate that they avoid poor RF coverage around 80% of the time. Internal walls, which can be made of concrete or cubicle panels, are hard to replicate. Additionally, the dynamic power level used by APs can vary based on how users are physically distributed around each AP.

The possibility of room layout changes between AP placement planning and installation is another issue. As a result, it go above and above to confirm that the installed APs offer the required coverage after a third-party company installs APs in accordance with the aforementioned rules.

Traditional RF Coverage Validation Is Time-consuming and Costly

There are two methods used to accomplish RF coverage validation:

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  • To mimic coverage, use a commercial software program; until to actively update it, it might not precisely represent the floor layout.
  • Walk around the floor with a client device. This takes a lot of time, though, and not all colleges have IT personnel on staff.

It created an internal substitute for walking the floor a few years back as weren’t happy with any of these two solutions. AP power levels and user counts per AP are shown in a dashboard by the specialized software. With a high power level and a large user base, it can search for indications of limited coverage APs.

This internal software wasn’t perfect, though. It had to manually get data from the WLAN controller throughout the whole organization every five minutes. In order to exclude non-prime-time data, set intriguing values, and account for regional variations, this also had to create complex algorithms (for instance, Friday is a working day in some places but not in others). Such human efforts are almost unachievable with hundreds of thousands of APs placed worldwide.

This method of network certification wastes valuable IT resources and is not scalable.

A Faster, Better Approach to Validation

A more affordable and scalable method of network validation is Intel Connectivity Analytics, which was recently created in partnership with Cisco and Intel’s Client Computing group.

It could only collect AP data before utilizing Intel Connectivity Analytics; To had no insight into the client side of things. It could learn about the number of users and transmit power level (Tx) from AP data, but it only utilized these details as indicators of poor coverage. Direct measurement of the coverage from the client’s point of view was not feasible.

Intel Connectivity Analytics, on the other hand, continuously collects data from the actual client devices. The real client experience is reflected in the client data.

For any client utilizing Intel Wi-Fi hardware and linked to a compatible Cisco wireless network
Image Credit To Cisco Blogs

For any client utilizing Intel Wi-Fi hardware and linked to a compatible Cisco wireless network, this solution offers detailed driver-level wireless client information. The APs automatically gather the Wi-Fi telemetry that clients send and securely send it to a Cisco Meraki Cloud management platform, Cisco Catalyst controller, or Cisco Catalyst Center management platform. After processing the data, the system provides network managers with insightful reports.

An effective, focused method is offered by Intel Connectivity Analytics, which detects low Received Signal Strength Indicator (RSSI) occurrences to identify users who are having trouble with their radio frequency. By looking at the particular AP power level history and deployment, to may investigate the problem immediately without having to gather and examine a large quantity of data.

Drilling down reveals that all of the low RSSI occurrences on a given day originate from the same AP.

Note: A higher negative value indicates a weaker signal. RSSI is measured in decibel milliwatts (dBm). An RSSI of -70 dBm, for instance, is stronger than one of -85 dBm. A powerful signal has an RSSI of -50 dBm, whereas a very faint signal has an RSSI of -85.

In conclusion

It can rapidly identify low-coverage regions and determine the cause with Intel Connectivity Analytics. It removes the need to manually gather and examine RF data from the whole organization or to roam the floor. Only where it matters can now concentrate the efforts.

There is a significant time savings. It may take 10 to 15 minutes to troubleshoot a connectivity issue on the client side without Intel Connectivity Analytics, and the IT administrator could only resolve one client at a time. The mean time to repair has been reduced to 10–15 seconds with the Intel Connectivity Analytics, and the system may concurrently identify many broken connections.

It may take days to identify the root cause of a spate of connection difficulties with a network. It can now identify the underlying cause of an issue in a couple of seconds to the Intel Connectivity Analytics. Furthermore, to no longer need to develop internal custom scripts and automated processes for gathering and maintaining client data, nor do need to maintain the own tool.

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