Tree-Structured Data Indexing for Networked Storage
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Solution Overview
Problem
Traditional data storage and transfer methods over networks are slow, especially for large data sets, leading to inefficiencies in sharing and backup processes, and can result in data loss due to overwriting or lockouts when multiple users access the same data simultaneously.
Innovation Solution
A method of indexing data objects using a tree configuration, where related data objects are clustered to minimize tree traversal, allowing for faster access and efficient data management, including the use of B+ trees for indexing and data stream management to optimize data storage and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored locally on local storage devices, then data access speed is improved, but data sharing and backup efficiency deteriorate
Solution Approach 1:
The patent segments data into data objects with unique identifiers and organizes them in a distributed networked storage system. Each data object can be independently accessed, shared, and backed up across multiple nodes in the network, enabling parallel operations that improve both access speed and sharing efficiency simultaneously.
Solution Approach 2:
The patent introduces an indexing system with tree configuration as an intermediary between data objects and storage locations. This index structure enables efficient location of data objects across the network without requiring full data transfers, thus improving both access speed and backup efficiency by reducing network traffic.
2Productivity
If data is transferred over the network, then data sharing is improved, but transfer speed deteriorates
Solution Approach 1:
The patent extracts only the essential identifying information (unique identifiers and location metadata) from data objects and stores it in an index structure. This allows the system to locate and access data objects without transferring the entire data objects over the network, significantly improving transfer speed while maintaining sharing efficiency.
Solution Approach 2:
The patent performs preliminary indexing of data objects at their storage locations before actual data access or transfer is needed. The tree-structured index pre-organizes data object locations and relationships, enabling rapid retrieval and minimizing network transfer requirements during actual data operations.
3Productivity
If multiple users access the same data simultaneously, then data sharing is improved, but data loss due to overwriting increases
Solution Approach 1:
The patent implements a version control system that tracks access and modification history of data objects. When multiple users access the same data, the system provides feedback about current versions and coordination status, enabling users to work cooperatively and preventing overwriting conflicts through automated version management and conflict detection.
Solution Approach 2:
The patent creates and manages copies of data objects with unique identifiers across the networked storage system. Instead of allowing direct simultaneous write access to the same data object, the system creates separate versioned copies that can be accessed and modified independently, then integrates changes through controlled merge processes, thus preventing data loss while maintaining sharing efficiency.
4Measurement precision
If a tree index structure is used, then data object location identification is improved, but tree traversal time increases
Solution Approach 1:
The patent optimizes the tree index structure by clustering data objects with similar characteristics or access patterns into specific branches of the tree. This creates local quality variations in the index where frequently accessed or related data objects are grouped together, reducing the average traversal distance and time while maintaining precise location identification capabilities.
Solution Approach 2:
The patent implements dynamic balancing and optimization of the tree index structure based on access patterns. The index adapts to changing data access behaviors by reorganizing nodes and branches to minimize traversal paths for frequently accessed data, thus reducing traversal time while preserving location precision. The index structure can be dynamically updated and rebalanced to optimize performance.
Data Source
AI summary
Data is stored and data objects are indexed by an index having a tree configuration and the tree is traversed to identify the location of a data object. Data objects are analyzed to assess the extent to which a second data object is related to a first data object, and locations of related data objects within the tree are clustered so as to minimize tree traversal when accessing data objects considered to be related.