Redundant IoT Device Deployment for Failure Replacement
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Solution Overview
Problem
Existing deployments of computing devices, particularly IoT devices, require human intervention for maintenance and remediation when failures occur, disrupting remote operation and convenience.
Innovation Solution
Implement a failure aggregator that catalogs device failures and uses a machine learning model to apply correction factors to redundant devices, enabling them to mimic the functionality of failed devices, thus maintaining operation without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant devices are deployed to replace failed devices automatically, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent deploys redundant devices in advance before failures occur, positioning them strategically within the deployment so they can immediately replace failed devices without requiring human intervention. The failure aggregator also performs preliminary analysis of failure patterns to optimize redundant device placement and configuration.
Solution Approach 2:
The patent creates redundant copies of computing devices that can serve as replacements when original devices fail. These copies maintain the necessary functionality to continue operations, effectively copying the operational capacity of failed devices to ensure continuous service delivery.
2Ease of operation
If machine learning models are used to generate correction factors, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The failure aggregator autonomously monitors device performance, detects failures, analyzes failure patterns using machine learning, and automatically generates correction factors without human intervention. The system serves itself by continuously learning from failure data and autonomously implementing remediation strategies through the deployed redundant devices.
Solution Approach 2:
The patent implements a feedback loop where the failure aggregator continuously collects data on device failures and operational status, analyzes this data using machine learning models to generate correction factors, applies these factors to redundant devices, and monitors the results to further refine future corrections. This closed-loop feedback system enables continuous improvement of failure management effectiveness.
3Reliability
If redundant devices are trained to mimic failed device functionality, then reliability is improved, but loss of time increases
Solution Approach 1:
Redundant devices are pre-configured with necessary software and operational parameters before failures occur. The failure aggregator maintains updated profiles of all devices in the deployment, so when a failure happens, the redundant device can be activated and begin mimicking the failed device's functionality immediately without requiring time-consuming training or configuration.
Solution Approach 2:
The failure aggregator creates detailed functional copies of failed devices by analyzing their operational patterns, data processing requirements, and communication protocols. These copies are pre-established in the redundant devices, enabling immediate assumption of failed device roles without real-time training, thus minimizing service interruption time.
Data Source
AI summary
Methods and systems for managing operation of a deployment are disclosed. The deployment may be managed by employing redundant devices within the deployment. The redundant devices may serve to replace operation of failed devices. Despite replacement of operations of a failed device, the redundant device may not have similar functionality as the failed device. To make the functionality similar to the failed device, a correction factor may be applied to the redundant device. In applying the correction factor, the output from the redundant device may be expected to match output from the failed device. In matching output from the failed device, the redundant device may operate in place of the failed device.