Samsung electronics co., ltd. (20240320111). METHOD AND DEVICE FOR PREDICTING ERRORS IN A COMPUTING SYSTEM simplified abstract
Contents
- 1 METHOD AND DEVICE FOR PREDICTING ERRORS IN A COMPUTING SYSTEM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND DEVICE FOR PREDICTING ERRORS IN A COMPUTING SYSTEM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Error Prediction Technology
- 1.13 Original Abstract Submitted
METHOD AND DEVICE FOR PREDICTING ERRORS IN A COMPUTING SYSTEM
Organization Name
Inventor(s)
Byungwoo Bang of Suwon-si (KR)
Jiyoon Lee of Uijeongbu-si (KR)
METHOD AND DEVICE FOR PREDICTING ERRORS IN A COMPUTING SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320111 titled 'METHOD AND DEVICE FOR PREDICTING ERRORS IN A COMPUTING SYSTEM
Simplified Explanation
The patent application describes a method and device for predicting errors in a computing system by analyzing log data and generating anomaly scores to determine the likelihood of future errors.
- Tokenizing log data into tokens
- Inputting tokens into a discriminator model to generate scores
- Determining anomaly score based on the scores
- Predicting likelihood of future errors in the computing system based on anomaly score
Key Features and Innovation
- Utilizes log data to predict errors in a computing system
- Discriminator model generates scores for tokens to identify anomaly tokens
- Provides a method for determining the likelihood of future errors based on anomaly scores
Potential Applications
- Predictive maintenance in computing systems
- Proactive error detection and prevention
- Enhancing system reliability and performance
Problems Solved
- Early detection of errors in computing systems
- Improving system stability and uptime
- Minimizing downtime and maintenance costs
Benefits
- Increased system reliability
- Reduced downtime and maintenance expenses
- Improved overall performance and efficiency
Commercial Applications
Predictive Maintenance Technology for Computing Systems: Enhancing Reliability and Performance
Prior Art
Further research can be conducted in the field of anomaly detection in computing systems to explore existing technologies and methods related to error prediction.
Frequently Updated Research
Stay updated on advancements in anomaly detection algorithms and predictive maintenance technologies for computing systems.
Questions about Error Prediction Technology
How does the discriminator model determine anomaly scores?
The discriminator model analyzes tokens from log data to generate scores indicating the probability of each token being an anomaly.
What are the potential implications of using this technology in large-scale computing systems?
This technology could significantly improve the reliability and performance of large-scale computing systems by proactively detecting and preventing errors.
Original Abstract Submitted
a method and device for predicting errors in a computing system are disclosed. the error prediction method includes: receiving log data generated by the computing system during operation of the computing system; tokenizing the log data into tokens; inputting the tokens to a discriminator model which generates scores of the respective tokens, each score corresponding to a probability that the corresponding token is an anomaly token; determining an anomaly score based on the scores; and determining a likelihood of future occurrence of an error in the computing system based on the anomaly score.
