Abstract: Multi-level machine learning models can be generated from the captured log events. Outcomes are predicted for input events in real-time. The captured log events are received and parsed to expose event outcome data. A first data set is generated by determining whether an outcome associated with the event outcome data was a success or a failure. Responsive to a failed event outcome, a second data set is generated by categorizing the failed event outcome, to train multiple level SVMs for prediction of Wi-Fi input events and automatic remediation of Wi-Fi issues.

Abstract: Multi-level machine learning models can be generated from the captured log events. Outcomes are predicted for input events in real-time. The captured log events are received and parsed to expose event outcome data. A first data set is generated by determining whether an outcome associated with the event outcome data was a success or a failure. Responsive to a failed event outcome, a second data set is generated by categorizing the failed event outcome, to train multiple level SVMs for prediction of Wi-Fi input events and automatic remediation of Wi-Fi issues.

Abstract: Wi-Fi channels are automatically selected in a WLAN controller based deployment. Scan results received from each of the plurality of access points comprise a list of neighboring access points from the plurality of access points relative to each access point. Responsive to a number of the plurality of access points exceeding a number of non-interfering channels, assigning each of the plurality of access points to a non-interfering channel with sharing of at least one of the non-interfering channels, using a GCA (Graph Coloring Algorithm) in which each color assignment corresponds to a non-interfering channel assignment in order to prevent neighboring access points from sharing a non-interfering channel. Lowest RSSI measurements collected by access points can also be a factor in channel selection.

Abstract: Wi-Fi channels are automatically selected in a WLAN controller based deployment. Scan results received from each of the plurality of access points comprise a list of neighboring access points from the plurality of access points relative to each access point. Responsive to a number of the plurality of access points exceeding a number of non-interfering channels, assigning each of the plurality of access points to a non-interfering channel with sharing of at least one of the non-interfering channels, using a GCA (Graph Coloring Algorithm) in which each color assignment corresponds to a non-interfering channel assignment in order to prevent neighboring access points from sharing a non-interfering channel. Lowest RSSI measurements collected by access points can also be a factor in channel selection.

Abstract: Wi-Fi channels are automatically selected in a WLAN controller based deployment. Scan results received from each of the plurality of access points comprise a list of neighboring access points from the plurality of access points relative to each access point. Responsive to a number of the plurality of access points exceeding a number of non-interfering channels, assigning each of the plurality of access points to a non-interfering channel with sharing of at least one of the non-interfering channels, using a GCA (Graph Coloring Algorithm) in which each color assignment corresponds to a non-interfering channel assignment in order to prevent neighboring access points from sharing a non-interfering channel. Lowest RSSI measurements collected by access points can also be a factor in channel selection.