Database Capacity Regulation via Execution Delay
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Solution Overview
Problem
Existing database systems lack the ability to dynamically adjust their capacity in response to changing user needs, leading to inefficiencies and the inability to optimize resource utilization, especially in environments where capacity must be flexible to meet varying demands.
Innovation Solution
Implementing a capacity management system that regulates access to resources such as processors and I/O operations, allowing for dynamic changes in computing capacity during runtime, even when the database is active, by delaying execution or adjusting clock speeds, and utilizing excess capacity to meet service level agreements and provide on-demand computing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If database systems provide fixed computing capacity, then system stability is maintained, but the ability to adapt to changing user needs deteriorates
Solution Approach 1:
The patent implements dynamic capacity adjustment by allowing the database system to change its computing capacity at runtime based on actual usage patterns and service level agreements. The capacity management system continuously monitors resource consumption and adjusts capacity allocation dynamically, transforming the static capacity model into a dynamic one that adapts to changing demands without requiring system redesign.
Solution Approach 2:
The capacity management system operates autonomously by automatically monitoring resource usage, evaluating service level agreement compliance, and adjusting capacity without manual intervention. The system self-regulates by identifying when capacity increases or decreases are needed based on actual usage patterns, eliminating the need for complex manual capacity planning and adjustment processes.
2Reliability
If database systems allocate excessive computing capacity, then service level agreements can be met, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the capacity management system continuously monitors actual resource usage and service level agreement compliance. Based on this feedback, the system automatically adjusts capacity allocation - increasing capacity when service levels are at risk and decreasing capacity when usage is low, ensuring optimal resource utilization while maintaining reliability.
Solution Approach 2:
The system dynamically changes capacity parameters based on monitored usage patterns and service level requirements. By adjusting computing capacity parameters in real-time rather than maintaining fixed over-provisioned capacity, the system ensures service level agreement compliance while minimizing wasted resources through parameter optimization.
3Productivity
If database systems reduce computing capacity, then resource utilization is optimized, but the ability to meet varying user demands deteriorates
Solution Approach 1:
The patent enables the database system to dynamically adjust capacity in response to varying user demands. The capacity management system continuously monitors demand patterns and automatically scales capacity up or down as needed, allowing the system to maintain high resource utilization efficiency while simultaneously responding flexibly to changing user requirements without manual intervention.
Data Source
AI summary
Capacity of a database system and/or a computing system that includes a database can be effectively changed from a current computing capacity to another computing capacity. This can be achieved by causing usage capacity of at least one of resource to be changed when the database is active. By way of example, capacity of a database system can be regulated by delaying the execution of the database work based on a target capacity. As a result, database work can take relatively longer to complete when the capacity of a database is effectively regulated to be below its full capacity. In effect, a portion of available capacity (excess capacity) can be made inaccessible to the database. However, excess capacity can be used to manage various services of the database in accordance with one or more service criteria (e.g., Service Level Goals or Agreements).