Adaptive Fault Recovery System for Server Command Prioritization
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Solution Overview
Problem
Existing fault recovery systems for data processors are inflexible and inefficient, as they cannot adapt to varying server conditions and often require manual adjustments, leading to prolonged downtime and increased maintenance costs due to repeated futile command executions and potential triggering of additional issues.
Innovation Solution
A fault recovery system that includes fault detecting means, command execution means, and decision means, which selects and optimizes fault restoration commands based on real-time server conditions and updates command execution orders based on past results, reducing downtime and maintenance costs by dynamically adjusting priority levels and command sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predetermined fault restoration commands are executed in a fixed order, then the system can automatically recover from failures, but the system cannot adapt to varying server conditions and operating performance changes over time
Solution Approach 1:
The patent implements dynamic command selection by updating the execution order of fault restoration commands based on past execution results and current server conditions. The system transitions from static predetermined command sequences to dynamic adaptive sequences that learn from historical data and adjust to changing server states, resolving the contradiction between adaptability and system complexity.
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring the execution results of fault restoration commands and using this information to update the command execution order. The decision means evaluates past results and adjusts future command selections accordingly, enabling the system to adapt to varying server conditions while maintaining automated operation.
2Adaptability or versatility
If manual adjustments are made to fault restoration commands to adapt to varying conditions, then the system can handle different server configurations, but maintenance cost increases substantially
Solution Approach 1:
The patent enables the fault recovery system to perform self-adjustment by automatically updating command execution orders based on past execution results. The decision means autonomously learns from historical data and modifies the command selection strategy without requiring manual intervention, thereby maintaining adaptability while eliminating the need for costly manual adjustments.
Solution Approach 2:
The system uses feedback from command execution results to automatically refine its decision-making process. By continuously learning from past outcomes, the system adapts to different server configurations autonomously, reducing maintenance costs while preserving adaptability to varying conditions.
3Reliability
If fault restoration commands are executed sequentially according to predetermined priority, then the system can systematically attempt recovery, but repeated futile command executions prolong downtime and may trigger additional troubles
Solution Approach 1:
The system performs preliminary evaluation of command suitability by analyzing past execution results before selecting the next command to execute. The decision means uses historical data to predict which commands are likely to be effective, avoiding futile executions and reducing downtime while maintaining systematic recovery approach.
Solution Approach 2:
The system incorporates feedback from previous command execution outcomes to dynamically adjust the selection of subsequent commands. By learning from past results, the system avoids repeating futile commands and selects more effective recovery actions, thereby reducing downtime while preserving reliability through systematic evaluation.
4Extent of automation
If the order of command executions is fixed, then the system can operate automatically without manual intervention, but the execution order cannot be optimized for individual server characteristics
Solution Approach 1:
The patent transforms the static fixed command execution order into a dynamic adaptive sequence that automatically adjusts based on learned patterns from past executions. The system maintains automated operation while incorporating customization to individual server characteristics through continuous learning and adaptation, resolving the contradiction between automation and adaptability.
Solution Approach 2:
The system uses feedback from execution results to automatically optimize the command execution order for individual server characteristics. The decision means learns from historical data and autonomously adjusts the sequence and selection of commands, maintaining full automation while achieving customization specific to each server's behavior patterns.
Data Source
AI summary
In a memory a number of entries are defined for mapping reference symptom levels of a server to fault restoration commands and to priority levels. In response to a status report from a fault detector indicating an operating state of the server, one of the commands is selected according to the priority levels corresponding to the reported state. The selected command is executed, and a result of the execution is estimated. In response to a subsequent status report, a comparison is made between the estimated result and an operating state indicated in the report. The priority levels are updated according to the comparison result. In a modification, status variables are mapped to the commands. A command is selected according to the status variables of entries to which a reported state corresponds. A success value is determined based on a result of execution of the command. The status variable of the selected command is updated with the determined success value.