Resource Failure Mitigation Through Predictive Checkpointing
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Solution Overview
Problem
Resource failure in distributed control systems (DCS) compromises system stability and availability, leading to potential data loss and performance degradation, especially when multiple failures occur.
Innovation Solution
A method for predicting resource failure using diagnostic data, persisting the service state through checkpointing, and restoring the service on a second resource using the persisted state, utilizing a checkpoint/restore workflow to minimize downtime and data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resource failure prediction and service restoration is implemented, then system resiliency and service continuity are improved, but system complexity and computational overhead increase
Solution Approach 1:
The system performs preliminary actions by predicting resource failures before they occur and persisting service states in advance. The failure prediction module analyzes diagnostic data to identify potential failures, and the service state persister saves container states before failure happens, enabling rapid restoration without complex real-time intervention
Solution Approach 2:
The patent introduces intermediary components including a failure prediction module that acts as a mediator between monitoring systems and restoration actions, and a service state persister that mediates between running services and restoration processes. These intermediaries manage the complexity by centralizing failure mitigation logic
2Loss of substance
If service state is persisted through checkpointing, then data loss is reduced, but storage requirements and processing overhead increase
Solution Approach 1:
The system extracts only the essential service state information that needs to be preserved for restoration, rather than persisting entire system states. The container state persister selectively saves critical data including process information, file descriptors, and network connections, reducing storage overhead while preventing data loss
Solution Approach 2:
The patent creates copies of container states through checkpointing, storing snapshots of running services that can be restored. This copying mechanism allows the system to preserve service states without duplicating entire system images, optimizing storage usage while enabling rapid restoration
3Reliability
If multiple simultaneous resource failures are handled, then system availability is maintained, but performance degradation increases due to workload redistribution
Solution Approach 1:
The system performs preliminary failure prediction and prepares restoration states before actual failures occur. When failures happen, pre-prepared service states are restored rapidly without requiring complex real-time workload redistribution, thus maintaining performance while ensuring availability
Solution Approach 2:
The patent implements dynamic resource allocation where services are restored to appropriate resources based on current system conditions. The system can dynamically select target resources for restoration and adjust workload distribution based on real-time capacity, preventing performance degradation from static redistribution strategies
Data Source
AI summary
A resource failure mitigation system and method for a distributed control system includes predicting failure of a first resource executing a service; persisting a state of the service; and restoring the service at a second resource using the persisted state.