Backup Scheduling via Dynamic Duration Prediction
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Solution Overview
Problem
Traditional data backup systems require frequent manual adjustments due to changing client environments and business impacts, leading to complex and high-cost configurations, and often result in incomplete backups within expected time windows, causing system imbalances and maintenance difficulties.
Innovation Solution
A method that determines the backup duration and time period for clients based on current attribute values and expected time windows, using a prediction model to automate scheduling and update data backup policies without extensive manual work, ensuring backups are completed within specified time frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustments are made frequently to adapt to changing client environments and business impacts, then the backup system can maintain adaptability, but the configuration complexity and maintenance cost increase significantly
Solution Approach 1:
The system automatically determines backup duration and schedules backup time periods based on current attribute values and expected time windows, eliminating the need for frequent manual adjustments. The backup management device autonomously adapts to changing client environments and business impacts by continuously monitoring attribute values and recalculating optimal backup parameters.
Solution Approach 2:
The backup duration and time period are dynamically determined based on current attribute values rather than being fixed manually. The system continuously updates backup parameters according to changing conditions, making the backup schedule flexible and adaptive without requiring complex manual reconfiguration.
2Adaptability or versatility
If manual backup scheduling is used to accommodate changing business needs, then flexibility is maintained, but the time and effort required for configuration and maintenance increase
Solution Approach 1:
The backup management device automatically determines backup durations and schedules time periods without human intervention. The system self-adjusts to changing business needs by monitoring attribute values and autonomously updating backup parameters, eliminating the time-consuming manual configuration process.
Solution Approach 2:
The system pre-determines backup durations based on current attribute values before execution, and pre-schedules backup time periods within expected time windows. This preliminary determination allows the system to automatically adapt to changing conditions without requiring real-time manual intervention during backup operations.
3Reliability
If backup policies are manually configured to meet expected time windows, then backup completeness can be ensured, but the system becomes difficult to maintain and update
Solution Approach 1:
The backup management device automatically maintains backup policies by continuously determining optimal durations and time periods based on current attribute values. The system self-updates backup configurations to ensure completion within expected time windows without requiring manual maintenance or intervention.
Solution Approach 2:
The system uses current attribute values as feedback to continuously adjust backup durations and time periods. By monitoring changes in attribute values and automatically recalculating optimal backup parameters, the system maintains reliable backup completion while adapting to changing conditions without manual intervention.
4Stability of the object's composition
If fixed backup schedules are used, then system stability is maintained, but the system cannot adapt to changing client environments and business impacts
Solution Approach 1:
The backup duration and time period are dynamically determined based on current attribute values rather than being fixed. The system maintains stability through automated, consistent determination processes while adapting to environmental changes by continuously updating parameters based on current conditions.
Solution Approach 2:
The system changes backup parameters (duration and time period) based on current attribute values to adapt to changing client environments and business impacts. By automatically adjusting these parameters rather than using fixed values, the system maintains both stability through systematic determination and adaptability to changing conditions.
Data Source
AI summary
According to example embodiments of the present disclosure, a method, device and computer program product for data backup are proposed. The method comprises: obtaining a respective current value of an attribute associated with a respective backup for at least one client in a backup system and an expected time window for performing the respective backup; determining a respective duration of the respective backup based on the respective current value; and determining a respective backup time period for performing the respective backup for the at least one client based on the respective duration and the expected time window. As such, the present solution may implement automatic backup scheduling.