Mobile Database Migration to Volatile Memory for Energy and Speed
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Solution Overview
Problem
Mobile device application performance is constrained by storage performance and data access, necessitating improved storage efficiency to reduce energy consumption and prevent bottlenecks.
Innovation Solution
A method that switches a mobile device from a default energy-consuming mode to an energy-saving mode by generating a data structure in volatile memory, copying data from a relational database, and converting access coding to optimize data access, using a combination of row-based and column-based storage techniques to minimize cache misses and select the most efficient data format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If data is accessed from non-volatile memory (first storage device), then energy consumption is reduced, but data access speed and application performance deteriorate
Solution Approach 1:
The patent segments the storage system into two distinct parts: non-volatile memory (first storage device) for energy-efficient data storage, and volatile memory (second storage device) for high-speed data access. This segmentation allows the system to leverage the advantages of both memory types by directing different operations to appropriate storage layers, thereby resolving the contradiction between energy consumption and access speed.
Solution Approach 2:
The volatile memory (second storage device) acts as an intermediary between the non-volatile memory and the mobile application. It temporarily holds copies of frequently accessed data, enabling fast access without requiring continuous access to the non-volatile memory, thus mediating between energy efficiency and access speed requirements.
2Speed
If data is copied to volatile memory (second storage device), then data access speed improves, but device complexity increases
Solution Approach 1:
The system employs a universal data structure format that can represent both relational database tables and columnar storage formats. This multi-functionality allows the same data structure to serve different purposes (storage and processing) without requiring separate complex mechanisms, thereby reducing overall system complexity while maintaining high access speeds.
Solution Approach 2:
The system implements automatic data copying and format conversion mechanisms that operate autonomously based on predefined criteria. The generation unit automatically creates data structures and copies data when switching to energy-saving mode, while the validation unit automatically verifies data integrity, eliminating the need for manual intervention and reducing operational complexity.
3Productivity
If automatic data copying and validation is implemented, then data access efficiency improves, but processing time during mode switching increases
Solution Approach 1:
The system performs preliminary actions by pre-defining data structure templates and validation rules before mode switching occurs. The generation unit has ready-made data structure schemas, and the validation unit has pre-configured validation logic, allowing rapid data copying and verification without extensive processing during the actual mode transition, thereby reducing switching time.
Solution Approach 2:
The system changes operational parameters by switching between different data storage modes (relational vs. columnar) and memory states (volatile vs. non-volatile). These parameter changes are optimized to minimize processing overhead, allowing the system to adapt its data access characteristics dynamically without requiring extensive reprocessing during mode transitions.
Data Source
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AI summary
Embodiments of the present invention provide a database migration and validation system including a migration framework which analyzes a relational database and its associated access coding and preprocessing coding, and based on these analyses generates an in-memory database, in-memory access coding, and in-memory database coding for a computer system. The migration and validation system may also include a validation framework which presents validation queries to the relational database and the in-memory database, compares the results of the queries, and reports the outcome of the comparison.