Juniper Networks, Inc.

Ebrahim S Safavi

Shmuel Shaffer

Mohammad Zohoorian

Techniques are described in which a network management system processes network event data received from the AP devices. The NMS is configured to dynamically determine, in real-time, a minimum (MIN) threshold and a maximum (MAX) threshold for expected occurrences for each event type, wherein the MIN thresholds and MAX thresholds define ranges of expected occurrences for the network events of the corresponding event types. The NMS applies an unsupervised machine learning model to the network event data to determine predicted counts of occurrences of the network events for each of the event types and identify, based on the predicted counts of occurrences and the dynamically-determined minimum threshold values and maximum threshold values for each event type, one or more of the network events as indicative of abnormal network behavior.

Virtual network assistant having proactive analytics and correlation engine using unsupervised ML model

A network management system may detect congestion and other network problems, identify the root cause of the issue and invoke remedial actions. The network management system may collect a time series of network data from various devices in the network. The network management system may use the collected network data to determine metrics indicating whether the network is experiencing congestion and/or anomalies, and if so, what is the root cause. Once the root cause is identified an automated and/or manual corrective action may take place.

Network anomaly detection and mitigation

A network management system (NMS) is configured to control roaming in a wireless network using a variable mobility threshold. For a first wireless device associated with a current location, the NMS obtains at least one performance metric of a first wireless signal received by the first wireless device at the current location from a first AP of a plurality of APs, compares the at least one parameter of the first wireless signal to at least one performance metric of a second wireless signal received by at least one other wireless device at the current location from a second AP of the plurality of APs, and triggers a roaming operation of the first wireless device from the first AP to the second AP if the comparison satisfies a mobility threshold that varies based on the at least one performance metric of the first wireless signal.

Control of roaming in a wireless network using a variable mobility threshold

Methods and apparatus for automatically identifying and correcting faults relating to poor communications service in a wireless system, e.g., in real time, are described. The methods are well suited for use in a system with a variety of access points, e.g., wireless and/or wired access points, which can be used to obtain access to the Internet or another network. Access points (APs), which have been configured to monitor in accordance with received monitoring configuration information, e.g. on a per access point interface basis, captures messages, store captured messages, and in collaboration with network monitoring apparatus which can be in an AP or external thereto, use message sequences to determine a remedial action to be automatically taken when poor service is likely as may be predicted based on the detected message sequence between a UE and one or more APs.

Methods and apparatus for facilitating fault detection and/or predictive fault detection

Methods and apparatus for identifying the root cause of deterioration of system level experience (SLE). Offending network components that caused the SLE deterioration are identified and corrective actions are taken.

Systems and methods for a virtual network assistant

One exemplary aspect describes systems and methods for determining normal SLE behavior, determining when a SLE exhibits abnormal deterioration, and determining whether to take an action to mitigate what appears to be an indication of an abnormal SLE.

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Santa Clara, CA, United States of America

Ebrahim S Safavi