Lumen Technologies had five patents in mobile during Q1 2024. Lumen Technologies Inc’s patents filed in Q1 2024 focus on improving computing services in distributed networks, optimizing video quality based on display capabilities, and implementing data validation and equipment failure prediction using blockchain technology. These patents introduce methods for predicting service requests, determining playback device characteristics for media content, and validating equipment output data for reliability. GlobalData’s report on Lumen Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Lumen Technologies grant share with mobile as a theme is 40% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Predictive resource allocation in an edge computing network utilizing machine learning (Patent ID: US20240086252A1)
The patent filed by Lumen Technologies Inc. focuses on improving computing services in a distributed network of remote computing resources, particularly edge nodes in an edge compute network. The technology involves aggregating historical request data, training a machine learning model, generating predictions for requested services, identifying edge nodes based on physical location, and allocating computing resources accordingly. The method aims to reduce latency by predicting and preparing for computing service requests before they are made, enhancing efficiency and responsiveness in providing services.
The patent outlines a computer-implemented method and system for optimizing computing services by leveraging historical data and machine learning models to predict and allocate resources for requested services. By training the machine learning model on historical request data, the technology can anticipate the type of service to be requested, the time of the request, and the location of the device making the request. This predictive approach allows for the proactive allocation of computing resources on identified edge nodes, reducing latency and improving the overall performance of computing services. The system includes multiple edge nodes with different physical locations, a processor, and memory storing instructions for executing operations related to training the machine learning model, generating predictions, identifying edge nodes, and allocating resources based on predicted service types and times.
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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.
