Juniper Networks had seven patents in big data during Q2 2024. Juniper Networks Inc filed patents in Q2 2024 for a performance monitoring system that uses machine learning to optimize metric collection intervals and alert rules. Another patent describes a fabric designer system that generates a user interface for designing data center fabrics based on user input and network device catalog. Additionally, techniques for EVPN Host Routed Bridging (HRB) and EVPN cloud-native data center with HRB are detailed, involving containerized user-level applications and a cloud native virtual router for communication of layer two network traffic. 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 big data 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 comprehensive monitoring. The method includes pull-based data collection processes, regression analysis for weight determination, and ongoing updates to sampling intervals. The patent also covers a computer-readable storage medium containing instructions for implementing the performance monitoring system, including collecting telemetry data, generating metric relevance attributes, determining predicted metric weights, and adjusting sampling intervals based on these predictions.
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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.
