International business machines corporation (20240193443). ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL simplified abstract
Contents
ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL
Organization Name
international business machines corporation
Inventor(s)
Nathan Andrew Phelps of Durham NC (US)
Ryan Anderson of Kensington CA (US)
Ashok Kumar Iyengar of Encinitas CA (US)
Kavitha Bade of Durham NC (US)
Joseph Andrew Pearson of Brookhaven GA (US)
Troy Fine of Sutter Creek CA (US)
ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240193443 titled 'ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL
Simplified Explanation: The patent application describes a method for deploying policies to edge devices in an edge computing environment using artificial intelligence reasoning models to analyze and understand the intent of the policy deployment. The method involves altering policies based on the analysis to optimize decision-making for edge devices.
- The method deploys policies to edge devices in an edge computing environment.
- Artificial intelligence reasoning models are used to analyze the policies and understand their intent.
- Weight values assigned to data points that do not apply to the current decision of an edge device are discounted.
- The policies are altered based on the analysis to improve decision-making for edge devices.
Potential Applications: This technology can be applied in various industries such as IoT, smart cities, healthcare, and manufacturing where edge computing is utilized. It can enhance the efficiency and effectiveness of decision-making processes in edge devices.
Problems Solved: - Optimizing policy deployment in edge devices - Improving decision-making processes using AI reasoning models - Enhancing the overall performance of edge computing environments
Benefits: - Increased efficiency in policy deployment - Enhanced decision-making capabilities for edge devices - Improved performance and reliability of edge computing systems
Commercial Applications: Title: Enhanced Policy Deployment for Edge Devices in Edge Computing Environments This technology can be commercially used in IoT devices, smart sensors, autonomous vehicles, and industrial automation systems. It can provide a competitive advantage by optimizing decision-making processes and improving overall system performance in edge computing environments.
Prior Art: Prior art related to this technology may include research papers, patents, or publications on AI-driven policy optimization in edge computing environments. Researchers and experts in the field of edge computing and artificial intelligence may have explored similar concepts.
Frequently Updated Research: Researchers are continuously exploring ways to enhance policy deployment and decision-making processes in edge computing environments using artificial intelligence. Stay updated on the latest advancements in AI-driven optimization for edge devices.
Questions about Edge Computing Optimization: 1. How does AI reasoning improve policy deployment in edge devices? 2. What are the key challenges in optimizing decision-making for edge computing environments?
Original Abstract Submitted
a computer-implemented method, according to one embodiment, includes deploying a policy to edge devices in an edge computing environment. the method further includes analyzing, using an artificial intelligence (ai) reasoning model, the policy to understand an intent of deploying the policy. the analyzing includes discounting a weight value assigned to data points that are determined to not apply to a current decision of a first of the edge devices. the method further includes causing the policy to be altered based on the analysis. a computer program product, according to another embodiment, includes a computer readable storage medium having program instructions embodied therewith. the program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.
