Binary Encoding Scheme for Efficient Data Transmission
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Solution Overview
Problem
Current data formats, such as XML, require excessive bandwidth and system overhead due to the need for frequent format transformations across multiple software modules and servers, leading to inefficiencies in data processing and communication in client-server architectures.
Innovation Solution
Implementing a binary encoding scheme that uses composite records with primitive data types, allowing for efficient data transmission and processing without the need for frequent format conversions, by including a message length field, binary format field, and value fields with type descriptors, lengths, and representations, enabling direct interpretation and processing at receiving servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If XML data format is used to represent information, then flexibility and ease of definition are improved, but bandwidth consumption and system overhead increase due to markup tags and format transformations
Solution Approach 1:
The patent extracts only the essential data elements from XML markup, eliminating redundant tags and formatting syntax. By representing data in a streamlined binary format that retains only the core information content, the system achieves flexibility comparable to XML while dramatically reducing bandwidth consumption and transmission overhead.
Solution Approach 2:
Instead of using text-based markup languages that require extensive tagging, the patent inverts the approach by using binary encoding where data is represented in its most compact form. This inversion from human-readable markup to machine-optimized binary representation eliminates the overhead of markup tags while maintaining data flexibility through structured field definitions.
2Adaptability or versatility
If data is transmitted in XML format with markup tags, then data can be flexibly formatted, but communication bandwidth is consumed excessively by tags rather than actual data
Solution Approach 1:
The patent extracts and removes all markup tag overhead from the data representation. By using a binary format that encodes only the essential data fields and their types without redundant syntactic elements, the system maintains formatting flexibility while eliminating the bandwidth consumption associated with XML tags and markup syntax.
Solution Approach 2:
The patent changes the parameter of data representation from text-based markup with high overhead to binary encoding with optimized field structures. This parameter change transforms the data format from one where tags consume significant bandwidth to one where the same formatting capability is achieved with minimal overhead by directly encoding field types, lengths, and values in binary form.
3Productivity
If multiple software modules transform data between different formats, then data can be processed by specialized modules, but format transformation overhead increases system complexity and reduces throughput
Solution Approach 1:
The patent creates a universal binary data format that can be directly processed by multiple software modules without requiring format transformations. This universal format serves multiple functions across different processing stages and modules, eliminating the need for specialized format conversion routines and reducing system complexity while maintaining the ability to handle diverse data types.
Solution Approach 2:
The patent applies preliminary action by encoding data in a standardized binary format at the source before transmission. This preliminary formatting ensures that data arrives at receiving modules in a universally processable form, eliminating the need for subsequent format transformations and reducing the complexity of data processing pipelines across multiple software modules.
4Adaptability or versatility
If numerical data is stored as character strings in XML, then data can be universally represented, but conversion overhead is required before numerical processing can occur
Solution Approach 1:
The patent changes the parameter of numerical data representation from character strings to native binary format. By encoding numerical values directly in binary form with explicit type descriptors, the system maintains universal representability across different data types while eliminating the time-consuming conversion overhead required when numerical data is stored as text and must be parsed and converted before processing.
Data Source
AI summary
A method and a system are provided for encoding and processing digital information. The digital information is encoded according to binary encoding formats corresponding to primitive data types. The primitive data types comprise scalar data types including Boolean, integer, float, decimal, time stamp, string, symbol, binary large object, and character large object data types. The primitive data types also comprise composite data types including structure, list and S-expression data types. The binary-encoded digital information is stored in a message with a predetermined format for transmission. No metadata is included in the message.