Dynamic Edge Policy Adjustment for Changing Computing Conditions
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Solution Overview
Problem
Existing multi-access edge computing solutions struggle to adapt dynamically to changing conditions, leading to inefficiencies and invalidation of predefined rules due to unanticipated scenarios, particularly in computation offloading and network topology changes.
Innovation Solution
A dynamic regulatory manager that collects context-aware parameters, generates and adjusts rules, and executes workflows to address changing conditions, using reinforcement and generative artificial intelligence for continuous learning and adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If predefined rules are used for edge computing policies, then initial system setup is simplified, but the system cannot adapt to unanticipated scenarios and changing conditions
Solution Approach 1:
The patent implements dynamic rule adjustment by allowing the system to modify edge computing policies in real-time based on changing conditions. The regulatory manager continuously monitors system state and updates rules dynamically, transforming the static predefined rule system into an adaptive dynamic system that can respond to unanticipated scenarios while maintaining operational simplicity.
Solution Approach 2:
The system incorporates feedback mechanisms where the regulatory manager monitors edge computing operations and uses this information to adjust rules. The feedback loop enables the system to learn from actual performance and changing conditions, continuously refining policies to maintain optimality without requiring complete reconfiguration of the initial system setup.
2Adaptability or versatility
If rules are dynamically adjusted to handle changing conditions, then adaptability improves, but system complexity increases
Solution Approach 1:
The patent introduces a regulatory manager as an intermediary component that handles the complexity of dynamic rule adjustment. This intermediary layer manages the intricate logic of monitoring, evaluating, and modifying rules, isolating the complexity from the core edge computing operations. The regulatory manager serves as a buffer that simplifies the interface between changing conditions and rule adjustments.
Solution Approach 2:
The system implements self-service capabilities where the regulatory manager automatically monitors conditions and adjusts rules without requiring manual intervention. The system serves itself by detecting changes in edge computing operations and autonomously modifying policies, reducing the operational complexity burden on users while maintaining high adaptability.
3Productivity
If computation offloading is implemented to reduce latency, then network efficiency improves, but system adaptability to topology changes deteriorates
Solution Approach 1:
The patent applies dynamic rule adjustment specifically to computation offloading policies, enabling the system to optimize network efficiency by offloading appropriate tasks while simultaneously adapting to network topology changes. The regulatory manager dynamically determines which computations to offload based on current network conditions, maintaining high productivity while preserving adaptability to structural changes.
Data Source
AI summary
Embodiments of the present invention provide computer-implemented methods, computer program product, and computer systems. One or more processors, collect information associated with a target edge platform. The one or more processors, generate a set of rules for a target edge platform for different situations that can occur on the target edge platform. The one or more processors in response to receiving additional information, dynamically adjust the generated set of rules for the target platform.