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Teleports SLE

SUMMARY Use the Teleports SLE to identify issues with location accuracy.

Teleports is one of the Location Service-Level Expectations (SLEs) that you can track on the Monitor page of the Juniper Mist™ portal. Understand what's measured by this SLE and what issues can contribute to a low SLE.

What Does the Teleports SLE Measure?

Juniper Mist identifies instances when the app client's estimated location veers away (or "teleports") from the actual location.

You can click the Settings button to set the number of meters to use as the success threshold for this SLE. The default is 3 meters, meaning that accuracy within 3 meters of the actual location is acceptable.

Classifiers for Excessive Teleports

When the Teleports SLE threshold is not met, Juniper Mist analyzes the data from the access points (APs) and the client devices and classifies the issues as follows.

  • Beacon Density—The app client detected a low number of beacons from the access points (APs).

  • Beam Density—The app client detected a low number of beams.

  • Machine Learning—Changes in machine learning affected location accuracy.

  • vBLE Placement—The placement of the APs affected location accuracy.

  • Device Sensor—Sensor issues in the device affected location accuracy with respect to motion, acceleration, etc.

  • Weak RSSI—The app client received a weak signal (low Received Signal Strength Indicator).

Example

Teleports SLE Example

  • Success Rate—On the left, you see that the threshold was met 77 percent of the time.

  • Timeline—In the middle, you can drag your mouse to see the success rate at each point in time. The example shows a 73 percent success rate at the selected time. To adjust the scope of the timeline, use the timeline drop-down list at the top of the Monitor page. For example, set the timeline to Today, Yesterday, This Week, or a custom date range.

  • Classifiers—On the right, you see a high-level root cause analysis for teleports that exceeded the threshold. In this example, the issues were attributed to Beam Density (33 percent), Beacon Density (33 percent), Weak RSSI (32 percent), and Machine Learning (2 percent). No issues (0 percent) were attributed to the other classifiers (0 percent).

Note:

You can click the Values button to show numbers instead of the success rate and classifier percentages. On the left, you see the average number of meters for teleports during the selected time period. In the middle, you see the number of meters for the selected moment. On the right, you see the number of excessive teleport issues per classifier.