Relational Data Storage Using String Buffers and Fixed Pointers
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Solution Overview
Problem
Mobile computing devices face limitations in processing power and memory capacity, necessitating efficient data storage solutions to enhance performance without increasing physical memory space.
Innovation Solution
A data structure utilizing expandable string buffers, tables, and indexes with uniform-sized pointers and compression techniques, allowing for constant time random access and minimizing memory usage by storing variable length fields in string buffers and maintaining records with B trees or B+ trees.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional database storage methods are used with variable length fields, then data flexibility is maintained, but memory storage space increases due to record headers and non-uniform record sizes
Solution Approach 1:
The database is segmented into two distinct parts: a fixed-size record structure containing uniform pointers, and a separate variable-length string buffer containing actual data values. This segmentation allows the record structure to have consistent size for efficient storage while the string buffer provides flexibility for variable length fields.
Solution Approach 2:
A string buffer acts as an intermediary between the fixed record structure and the variable length data fields. The string buffer stores all variable length field values and provides a unified interface for accessing data of varying lengths, eliminating the need for variable length record structures.
2Loss of time
If records with variable length fields are stored directly, then data representation is straightforward, but random access time increases due to non-uniform record sizes
Solution Approach 1:
The patent changes the parameter of record size from variable to fixed by using uniform pointers of consistent size (e.g., 4 bytes) to reference variable length data in the string buffer. This parameter change enables constant time random access while maintaining the ability to represent variable length data.
Solution Approach 2:
The patent separates the data storage dimension from the indexing dimension. The fixed record structure in one dimension provides uniform access patterns, while the string buffer in another dimension stores variable length data. This dimensional separation allows efficient random access without compromising data representation flexibility.
3Quantity of substance
If physical memory space is enlarged to store more data, then data capacity increases, but processing power requirements and device performance are compromised on mobile devices
Solution Approach 1:
The patent changes the parameter of memory utilization efficiency by using compact fixed-size pointers instead of variable length records. This parameter change increases the amount of data that can be stored in a given memory space, effectively increasing data capacity without requiring additional physical memory or processing resources.
Data Source
AI summary
An efficient method for storing relational data in a memory space uses B tree and B+ tree structures to store data for a database where non-identical values are stored in a string buffer and pointers to the string buffer are stored in a table buffer, and where identical data is stored only once, and each instance of that value in the database is referenced by a pointer to such identical data corresponding to the locations in the database where that identical value exists, thereby preserving physical memory and increasing the storage capacity of a fixed memory space.