Level 3 Communications, LLC (20240232621). ENHANCED TESTING OF PERSONALIZED SERVERS IN EDGE COMPUTING simplified abstract
Contents
ENHANCED TESTING OF PERSONALIZED SERVERS IN EDGE COMPUTING
Organization Name
Inventor(s)
Bryan Dreyer of Bellevue WA (US)
James Sutherland of Ridgefield WA (US)
ENHANCED TESTING OF PERSONALIZED SERVERS IN EDGE COMPUTING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240232621 titled 'ENHANCED TESTING OF PERSONALIZED SERVERS IN EDGE COMPUTING
The patent application describes a system for testing servers provisioned in an edge computing device by using a neural network to evaluate the performance of the server.
- Edge computing device detects server provisioned to access public network cloud
- Neural network evaluates probability of server performance meeting criteria
- Neural network trained on labeled settings data and feature weights
- Inputs settings and configurations associated with server provisioning to neural network
- Generates confidence score based on inputs and training data
Potential Applications: - Quality assurance for servers provisioned in edge computing devices - Predictive maintenance for server performance optimization
Problems Solved: - Ensures servers meet performance criteria before deployment - Improves efficiency and reliability of edge computing systems
Benefits: - Reduces downtime and maintenance costs - Enhances overall performance of edge computing infrastructure
Commercial Applications: Optimizing server performance in edge computing devices can benefit industries such as telecommunications, IoT, and cloud computing by ensuring reliable and efficient operations.
Questions about the technology: 1. How does the neural network determine the probability of server performance? 2. What are the key factors considered in the training data for the neural network?
Frequently Updated Research: Stay updated on advancements in neural network training methods for server performance evaluation in edge computing devices.
Original Abstract Submitted
this disclosure describes systems, methods, and devices related to testing servers provisioned in an edge computing device. an edge computing device may detect that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device; provide a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights; input settings and configurations associated with the provisioning of the server as inputs to the neural network; and generate, using the neural network, based on the inputs and the training data, a confidence score indicative of the probability.
