Adaptive Schema Compression for Bandwidth and Processing Overhead
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Solution Overview
Problem
Existing systems face significant overhead in bandwidth, time, and processing power due to the large size of schemas, which are often transmitted with data, leading to inefficient resource utilization.
Innovation Solution
An adaptive compression technique is applied to schemas based on their content, using algorithms like shoco, Huffman, or SMAZ to determine whether to apply short text or text compression, reducing the schema size by up to 50% and minimizing network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If schemas are transmitted without compression, then data integrity and completeness are maintained, but bandwidth usage and transmission time increase significantly
Solution Approach 1:
The patent applies compression algorithms that transform the schema data from an uncompressed state to a compressed state, changing the size parameter while maintaining data integrity. The system selectively applies compression based on schema characteristics, transforming the data representation to reduce bandwidth consumption.
Solution Approach 2:
The patent creates a compressed copy of the schema data that can be transmitted instead of the original. This compressed representation contains all necessary information in a reduced form, allowing the system to work with a copy rather than the full-size original during transmission.
2Loss of time
If compression algorithms are applied to schemas, then bandwidth usage and transmission time are reduced, but processing overhead and computational resources increase
Solution Approach 1:
The patent applies different compression strategies based on the local characteristics of the schema data. Rather than applying a uniform compression approach, the system analyzes schema-specific properties and selects appropriate compression methods, optimizing the balance between compression ratio and processing overhead for each specific case.
Solution Approach 2:
The patent applies compression selectively rather than universally. The system determines when compression is beneficial based on schema characteristics and transmission requirements, applying compression only in cases where the benefit outweighs the processing cost, thus avoiding excessive processing for schemas that would not benefit from compression.
3Productivity
If selective compression is applied based on schema analysis, then resource utilization is optimized, but system complexity increases
Solution Approach 1:
The patent performs preliminary analysis of the schema to determine whether compression is appropriate before actually applying compression. This advance assessment allows the system to make informed decisions about compression application, avoiding the complexity of real-time decision-making during transmission and simplifying the overall system architecture.
Data Source
AI summary
A system includes a memory and a processor, where the processor is in communication with the memory. The processor is configured to receive a request to compress a schema. The schema is analyzed to determine whether to apply a first type of compression or a second type of compression, where analyzing the schema includes determining whether the schema exceeds a threshold level. Upon determining that the schema exceed the threshold level, a compressed schema is generated by performing the second type of compression. Next, the processor responds to the request with the compressed schema.