Dynamic Data Protection Scheduling Based on Object Activity
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Solution Overview
Problem
Existing data protection processes face challenges in determining an appropriate time interval for data backup, leading to excessive resource consumption if the interval is too small or inadequate data restoration if it is too large.
Innovation Solution
A method and system that monitor and evaluate the activity of data objects to dynamically schedule data protection processes, prioritizing frequently accessed files for more frequent backups and less accessed files for less frequent backups, using a weighted calculation of read and write operations to determine a 'hotness' score that dictates the backup frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the data protection interval is set to be small, then data restoration capability is improved, but system resource consumption increases
Solution Approach 1:
The patent applies local quality by differentiating data protection frequency based on individual data object characteristics. Each data object receives a customized protection interval according to its activity level (hot, warm, cold), rather than applying a uniform interval to all data. This resolves the contradiction by concentrating protection resources on frequently accessed data while reducing protection frequency for rarely accessed data.
Solution Approach 2:
The patent implements dynamics by making the data protection interval adaptive rather than static. The system continuously monitors data object activity and dynamically adjusts protection intervals in response to changing access patterns. This allows the system to optimize between restoration capability and resource consumption by adapting to actual data usage needs.
2Use of energy by moving object
If the data protection interval is set to be large, then system resource consumption is reduced, but data restoration capability deteriorates
Solution Approach 1:
The patent applies local quality by differentiating data protection frequency based on individual data object characteristics. Each data object receives a customized protection interval according to its activity level (hot, warm, cold), rather than applying a uniform interval to all data. This resolves the contradiction by concentrating protection resources on frequently accessed data while reducing protection frequency for rarely accessed data.
Solution Approach 2:
The patent implements dynamics by making the data protection interval adaptive rather than static. The system continuously monitors data object activity and dynamically adjusts protection intervals in response to changing access patterns. This allows the system to optimize between restoration capability and resource consumption by adapting to actual data usage needs.
3Adaptability or versatility
If manual frequency setting is required, then data protection can be customized, but system complexity and operational difficulty increase
Solution Approach 1:
The patent applies self-service by enabling the system to automatically determine and adjust data protection intervals based on monitored data object activity. The system self-configures protection frequencies without requiring manual user input, eliminating the contradiction between customization capability and operational simplicity. Users benefit from adaptive protection without the burden of manual configuration.
Solution Approach 2:
The patent implements feedback by continuously monitoring data object access patterns and using this information to automatically adjust protection intervals. The system observes actual data usage and responds by optimizing protection frequency, replacing manual configuration with an automated feedback-driven process that adapts to changing conditions.
Data Source
AI summary
There is disclosed a method, a system, and a computer program product suitable for backing up data on a computer system. In at least one embodiment, the method comprises monitoring activity in connection with a plurality of data objects. The method also comprises determining a level of activity in connection with each data object. The method further comprises evaluating the level of activity in connection with each data object. The method still further comprises scheduling a data protection process in connection with at least one of the data objects based on the said evaluation.


