Network Device Reboot Logging and Cause Analysis

The patent applies preliminary action by persistently storing reboot cause information in a database before it can be lost. The system detects reboot causes by analyzing log files and immediately stores them in a persistent database, ensuring that historical reboot information is captured and preserved for future analysis, preventing information loss.

The patent uses copying by creating a persistent copy of reboot cause information in a database. Instead of only maintaining transient log files that may be overwritten, the system creates a permanent copy of each reboot cause entry in a structured database format, enabling long-term storage and analysis of reboot history.

The patent applies segmentation by dividing the logging system into distinct functional components: a detection module that identifies reboot events, an analysis module that determines reboot causes from log files, and a storage module that persists information in a database. This segmentation allows each component to be optimized independently, improving reliability while managing complexity through modular design.

The patent uses an intermediary approach by introducing a database as a mediator between the reboot detection/analysis processes and the long-term storage requirements. The database serves as an intermediary layer that structures and persists reboot cause information, enabling reliable historical analysis without requiring direct complex integration between all system components.

The patent applies preliminary action by performing log file analysis immediately when a reboot is detected, before the log files may be overwritten or lost. The system proactively analyzes the log files and extracts reboot causes while the information is still available, ensuring accurate identification without delaying the logging process.

The system performs self-service by automatically analyzing its own log files to determine reboot causes without requiring external intervention. The logging system independently processes its own data, extracts meaningful information, and stores the results, eliminating the need for manual analysis and reducing overall processing time.