Endpoint Device Drift Management via Digital Twin Feedback
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Solution Overview
Problem
Device drift over time leads to deviations in the operation of endpoint devices from their expected nominal conditions, affecting the performance of computer-implemented services.
Innovation Solution
A method and system for managing device drift by monitoring endpoint devices, characterizing drift through digital twins that incorporate environmental and component conditions, and selecting and performing actions to mitigate or compensate for drift, using a graphical user interface to facilitate user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If endpoint devices operate autonomously over time, then device independence and deployment flexibility are improved, but device drift from nominal conditions occurs affecting service performance
Solution Approach 1:
The system continuously monitors endpoint device characteristics and compares them against nominal conditions stored in the digital twin. When drift is detected, the system generates feedback signals that trigger remediation actions to restore nominal operation, creating a closed-loop control system that maintains reliability while allowing autonomous operation.
Solution Approach 2:
A digital twin (copy) of the endpoint device's nominal state is created and maintained in the management system. This digital copy contains baseline characteristics and expected performance parameters that are used to detect and correct drift in the actual device, enabling autonomous operation while maintaining service performance through comparison with the idealized copy.
2Reliability
If device drift is monitored and managed, then service performance is maintained, but system complexity increases due to digital twins and monitoring infrastructure
Solution Approach 1:
Instead of managing physical device states directly, the system creates and manages digital twins (virtual copies) of nominal device conditions. These digital representations simplify monitoring and analysis by providing a standardized, accessible model of expected behavior that can be compared against actual device performance without physically modifying or complicating the endpoint devices.
Solution Approach 2:
The digital twin serves as an intermediary between the endpoint device and the management system. It mediates the complexity by providing a standardized interface for monitoring device characteristics, storing nominal conditions, and generating remediation actions, thereby simplifying the overall system architecture while maintaining reliable service performance.
3Reliability
If remediation actions are automatically performed, then drift impact is reduced, but loss of operational control by users occurs
Solution Approach 1:
The remediation system is designed to be dynamic and adaptive rather than purely automated or purely manual. The system can automatically execute remediation actions when drift is detected, but also provides interfaces for user review, modification, or approval of actions. This dynamic approach allows the system to adapt to different operational contexts and user preferences, maintaining both effectiveness and user control.
Data Source
AI summary
Methods and systems for manage operation of endpoint devices are disclosed. To manage the operation of endpoint devices, drift in the endpoint devices may be monitored. The monitoring be used to granularly characterize different types of drift impacting the endpoint device, and quantify the level of each type of drift experienced by the endpoint devices. The types and quantifications may be used to select actions to perform to manage the drift. By managing the drift, the impact of the drift on operation of the endpoint devices may be reduced.