Graph Database Traversal via Binary Encoding
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Solution Overview
Problem
Current graph database traversal methods in computer network operating systems are inefficient due to the need for lengthy string-based operations and path validation, leading to high runtime costs and resource overhead.
Innovation Solution
The implementation of a binary-encoded traversal specification and execution engine (GREEN) that generates database instructions for a target node, allowing for rapid navigation through a graph database using binary-encoded operation codes, node traversal lists, and parameters, eliminating the need for URI input and enabling in-service software upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If string-based operations and path validation are used for graph database traversal, then the system maintains ease of operation with URI input, but execution time and resource usage increase significantly
Solution Approach 1:
The patent changes the parameter representation from string-based URIs to binary-encoded traversal specifications. This parameter transformation eliminates parsing overhead and enables direct interpretation by the execution engine, significantly reducing execution time while maintaining the same functional capability of specifying database traversal paths
Solution Approach 2:
The patent replaces the mechanical string parsing and validation process with a binary-encoded system that can be directly processed by the execution engine. This substitution eliminates the need for text-based operations, type conversions, and path validation, achieving faster performance through a more efficient processing mechanism
2Ease of operation
If string-based operations and path validation are used for graph database traversal, then the system maintains ease of operation with URI input, but resource overhead increases
Solution Approach 1:
The patent transforms the input parameter format from verbose string-based URIs to compact binary-encoded representations. This parameter change reduces memory usage during traversal operations and minimizes the computational resources required for parsing and validation, directly addressing the resource overhead problem
3Productivity
If binary-encoded traversal specification is used, then execution time and resource usage are reduced, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary execution engine that translates binary-encoded traversal specifications into database operations. This intermediary layer handles the complexity of binary interpretation and traversal execution, allowing the client interface to remain simple while achieving high performance through optimized internal processing
Data Source
AI summary
In one embodiment, an operating system on a computer device interfaces with a graph database that has data nodes interconnected by relationship edges. The operating system generates database instructions that specify a database operation for a target node in the graph database and a node traversal list through the graph database to reach the target node. By then transmitting the database instruction to the graph database, the graph database (e.g., a database management operating system) traverses the specified node traversal list through the graph database to the target node, and performs the database operation on the target node.