Lumen Technologies had two patents in edge computing during Q1 2024. Lumen Technologies Inc’s patents filed in Q1 2024 focus on improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. The technology involves aggregating historical request data, training a machine learning model, generating predictions for types of services, identifying edge nodes based on physical location, and allocating computing resources accordingly. Additionally, a tool is provided to configure an edge compute environment by generating a configuration process based on user input and databases, automatically executing configuration instructions, and utilizing micro-services to communicate with and control device configuration. 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 had no grants in edge computing as a theme in Q1 2024.
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 service provision.
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 future service requests. By training the machine learning model on aggregated 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. Additionally, the system includes various components such as edge nodes with different physical locations, processors, and memory to execute the operations efficiently, ensuring seamless service delivery based on predicted demands.
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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.
