Juniper Networks had 45 patents in artificial intelligence during Q2 2024. Juniper Networks Inc filed patents in Q2 2024 for a performance monitoring system that includes metric collection, alert rule evaluation, and machine learning capabilities. Another patent describes an analysis system for software-defined networking architecture, identifying dependencies and potential issues. Additionally, patents were filed for processing signals from beacon transmitter devices for location determinations based on motion, and methods for detecting misconfigured VLANs across network components. Lastly, a network management system patent was filed for detecting congestion, identifying root causes, and invoking remedial actions based on collected network data. GlobalData’s report on Juniper Networks gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Juniper Networks had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Machine learning for metric collection (Patent ID: US20240211368A1)
The patent filed by Juniper Networks Inc. describes a performance monitoring system that collects telemetry data related to a network of computing devices, stores metrics in a database, and evaluates alert rules using stored metrics. The system includes a machine learning module to determine optimized metric collection sampling intervals, rule evaluation intervals, and recommend alert rules automatically. The method involves collecting metric values at different intervals, generating metric relevance attributes, determining predicted metric weights, and collecting additional telemetry data based on these weights. The system also determines critical metrics and adjusts sampling intervals accordingly, uses machine learning models for predictions, and updates sampling intervals continuously.
The performance monitoring system and method described in the patent involve collecting telemetry data, storing metrics, and evaluating alert rules using machine learning techniques. The system adjusts collection sampling intervals based on predicted metric weights, determines critical metrics for priority sampling, and identifies related metrics for analysis. The method includes pull-based data collection processes, regression analysis for weight determination, and ongoing updates to sampling intervals. The patent also covers computer-readable storage media with instructions for implementing the performance monitoring system, including determining critical metrics, adjusting sampling intervals, and analyzing related metrics based on access ratios.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
