International Business Machines Corporation (20240330715). DIGITAL TWIN BASED DATA DEPENDENCY INTEGRATION IN AMELIORATION MANAGEMENT OF EDGE COMPUTING DEVICES simplified abstract
DIGITAL TWIN BASED DATA DEPENDENCY INTEGRATION IN AMELIORATION MANAGEMENT OF EDGE COMPUTING DEVICES
Organization Name
International Business Machines Corporation
Inventor(s)
Atul Mene of Morrisville NC (US)
Jeremy R. Fox of Georgetown TX (US)
Tushar Agrawal of West Fargo ND (US)
Sarbajit K. Rakshit of Kolkata (IN)
DIGITAL TWIN BASED DATA DEPENDENCY INTEGRATION IN AMELIORATION MANAGEMENT OF EDGE COMPUTING DEVICES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240330715 titled 'DIGITAL TWIN BASED DATA DEPENDENCY INTEGRATION IN AMELIORATION MANAGEMENT OF EDGE COMPUTING DEVICES
Simplified Explanation: The patent application describes a method, program, and system for managing edge computing devices by generating digital twin models of the devices, predicting health issues, reassigning computing loads, and removing dependencies to ensure smooth operation.
Key Features and Innovation:
- Generation of digital twin models for edge devices
- Prediction of impacted devices and impact occurrence time
- Reassignment of computing loads based on simulations
- Ensuring completion of remaining loads on impacted device
- Removal of dependencies on impacted device
Potential Applications: This technology can be applied in various industries such as manufacturing, healthcare, transportation, and smart cities to optimize edge computing operations and enhance device performance.
Problems Solved: The technology addresses issues related to predicting and managing health problems in edge devices, optimizing computing loads, and ensuring uninterrupted operation of edge computing systems.
Benefits:
- Improved efficiency and performance of edge devices
- Enhanced reliability and stability of edge computing systems
- Reduction of downtime and maintenance costs
- Better resource allocation and workload management
Commercial Applications: The technology can be utilized by edge computing providers, IoT companies, and businesses relying on real-time data processing to streamline operations, improve productivity, and deliver better services to customers.
Prior Art: Readers can explore existing patents and research on edge computing, digital twin technology, predictive maintenance, and workload optimization to understand the background and evolution of similar concepts.
Frequently Updated Research: Stay informed about the latest developments in edge computing, digital twin modeling, predictive analytics, and workload management to leverage cutting-edge technologies for business growth and innovation.
Questions about Edge Computing Management: 1. How does the technology of digital twin models benefit edge computing management? 2. What are the potential challenges in implementing predictive maintenance for edge devices?
Original Abstract Submitted
a computer-implemented method, a computer program product, and a computer system for amelioration management of edge computing devices. a computer generates digital twin models of respective ones of edge devices. a computer uses the digital twin models to predict an impacted edge device which has a health issue in edge computing. a computer uses the digital twin models to predict impact occurring time. a computer, based on simulations with the digital twin models, reassign a portion of edge computing loads that originally assigned to the impacted edge device to other edge devices. a computer keeps remaining edge computing loads on the impacted edge device such that the impacted edge device is able to complete the remaining edge computing loads prior to the impact occurring time. a computer removes dependencies of the other edge devices on the impacted edge device, in response to the remaining edge computing loads being completed.
