Optimization System for Database Query Routing
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Solution Overview
Problem
Current client-server systems face performance issues when operating over slow network connections, limiting the sophistication of web applications and requiring either local network connections for richness or remote connections with poor functionality.
Innovation Solution
A method optimizing interactions between client and database server software by routing query and response data through an optimization system that analyzes and applies rules to reduce data processing and transmission, enabling efficient communication over slow links like the Internet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If client-server systems operate over slow network connections, then accessibility and remote functionality are improved, but performance and data exchange speed deteriorate
Solution Approach 1:
The optimization system performs preliminary actions by analyzing query data before it reaches the database server and applying optimization rules in advance. This includes decoding query data, understanding its content and context, and pre-processing response data to reduce the actual data transmission time over the slow network connection.
Solution Approach 2:
An optimization system is introduced as an intermediary component between the client application and the database server. This mediator routes query data from the client to the server and response data back to the client, applying optimization rules at each stage to improve overall system performance over remote connections without requiring changes to the existing client-server architecture.
2Quantity of substance
If data is compressed and optimized for transmission, then network bandwidth usage is reduced, but processing time and complexity increase
Solution Approach 1:
The optimization system changes parameters of the data by decoding query data to understand its content and context, then applying specific optimization rules that transform the data into more efficient formats for transmission. This includes modifying response data parameters to reduce size while maintaining integrity, balancing compression benefits against processing overhead.
3Adaptability or versatility
If cloud-based database systems are implemented, then infrastructure flexibility and accessibility are improved, but network dependency and performance issues worsen
Solution Approach 1:
The optimization system implements feedback mechanisms by analyzing the effectiveness of applied optimization rules and using this information to improve future optimizations. The system monitors performance metrics and adjusts its optimization strategies accordingly, creating a self-improving system that adapts to specific cloud-based database interactions and network conditions.
Data Source
AI summary
The invention is a method of optimizing the interaction between (i) a client, being an application such as database software, implemented on a computing device, and (ii) database server software implemented on a computing device. Query data is routed from the client to the database server software through an optimization system implemented on a computing device and then response data provided by the database server software is routed to the optimization system. The optimization system analyzes that (or later) query data and, based on that analysis, applies rules to response data provided by the database server software, in order to generate optimized response data to thereby speed up the interaction between the client and the database server software.