Abstract: Wi-Fi access point performance management may include receiving a session analytic record related to a plurality of wireless access points, and analyzing the session analytic record related to the plurality of wireless access points to determine a root cause of at least one malfunctioning node related to at least one of the plurality of wireless access points, and predict failure of the at least one of the plurality of wireless access points. Further, a graphical user interface display or a report may be generated. The graphical user interface display or the report may be related to the determination of the root cause of the at least one malfunctioning node related to the at least one of the plurality of wireless access points, and prediction of the failure of the at least one of the plurality of wireless access points.

Abstract: In an example, a performance of an access point in a wireless network is optimized based on a statistical ranking of independent variables. A device analyzer may calculate a dependent variable for the performance of the access point and independent variables that impact the dependent variable from a set of independent variables based on real-time access point data received from a plurality of access points. A predictive modeler may generate a model to forecast the performance of the access point and to determine an impact ranking for the independent variables from the dependent and independent variables. The impact ranking may sequence the independent variables according to their impact on the dependent variable. Accordingly, a configuration circuit may adjust a controllable parameter of the access points according to the impact ranking.

Abstract: Wi-Fi access point performance management may include receiving a session analytic record related to a plurality of wireless access points, and analyzing the session analytic record related to the plurality of wireless access points to determine a root cause of at least one malfunctioning node related to at least one of the plurality of wireless access points, and predict failure of the at least one of the plurality of wireless access points. Further, a graphical user interface display or a report may be generated. The graphical user interface display or the report may be related to the determination of the root cause of the at least one malfunctioning node related to the at least one of the plurality of wireless access points, and prediction of the failure of the at least one of the plurality of wireless access points.

Abstract: In an example, a performance of an access point in a wireless network is optimized based on a statistical ranking of independent variables. A device analyzer may calculate a dependent variable for the performance of the access point and independent variables that impact the dependent variable from a set of independent variables based on real-time access point data received from a plurality of access points. A predictive modeler may generate a model to forecast the performance of the access point and to determine an impact ranking for the independent variables from the dependent and independent variables. The impact ranking may sequence the independent variables according to their impact on the dependent variable. Accordingly, a configuration circuit may adjust a controllable parameter of the access points according to the impact ranking.