Constrained Message Encoding Using Preconfigured Reduced-Type Templates
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Solution Overview
Problem
In tactical telecommunications, existing messaging systems face challenges in minimizing data size for constrained applications, ensuring interoperability, and maintaining a sustainable reference system, particularly due to limited bit rate and resource constraints, which complicates the transmission of messages with reduced byte sizes and affects the evolution of messaging systems.
Innovation Solution
A method for generating a library of optimized messages by defining a descriptor with reduced types, transforming it into a preconfigured message repository, and instantiating messages to minimize data size while ensuring compatibility and durability, involving the selection, truncation, or extraction of original types to fit limited byte constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If message encoding is optimized to reduce byte size for constrained bit rate transmission, then data transmission efficiency is improved, but interoperability between different communication entities deteriorates and system evolution becomes complex
Solution Approach 1:
The message encoding system is segmented into multiple layers: a standardized header portion and a flexible payload portion. The header contains fixed-format fields for message type, length, and routing information that ensure interoperability, while the payload can be dynamically optimized for specific applications. This segmentation allows different entities to agree on common protocols while optimizing individual message formats.
Solution Approach 2:
The system employs variable parameter encoding where data types and field lengths are dynamically adjusted based on message requirements. Instead of fixed-size fields, the encoding adapts parameters such as integer precision, string length, and optional field inclusion to match the actual data being transmitted. This reduces average message size while maintaining compatibility through a standardized encoding framework.
2Quantity of substance
If message encoding is optimized to reduce byte size, then transmission bandwidth requirement is reduced, but message definition complexity and labor increase
Solution Approach 1:
Message templates and encoding schemas are pre-defined and standardized before actual message transmission. Common message types (e.g., position reports, status updates, commands) have predetermined optimal encodings that have been analyzed and fixed in advance. This preliminary standardization eliminates the need for complex real-time optimization while maintaining small message sizes.
Solution Approach 2:
Instead of defining unique optimized encodings for each message type, the system uses templates and patterns that can be copied and reused. A library of standardized message templates exists, where common structures can be instantiated and modified minimally for specific needs. This copying approach reduces definition complexity while maintaining optimization benefits.
3Loss of information
If comprehensive message information is transmitted to ensure complete data representation, then information accuracy is improved, but transmission time and data volume increase
Solution Approach 1:
Different portions of the message have different quality requirements. The system applies differential encoding where critical fields (e.g., position coordinates, timestamp, message type) use higher precision encoding, while less critical fields (e.g., descriptive text, optional parameters) use compressed or abbreviated encoding. This local quality adjustment maintains information accuracy where needed while reducing overall message size.
Solution Approach 2:
The system transmits only the necessary portion of information based on message type and context. Optional fields are included only when relevant, and precision levels are adjusted to the minimum required for the application. This partial action approach avoids transmitting excessive data while ensuring all critical information is present.
Data Source
Figure 1
Figure 2A~2C
AI summary
The process of generating a data set defining a message (MES) includes: ▪ A definition of a first descriptor (DESCR_1) of a message set (MES), each message (MES) having a set of attributes each having a reduced type (TYP_RED), said descriptor (DESCR_1) also describing the set of reduced types, each reduced type (TYP_RED) being encoded from an original type (TYP_ORI); ▪ A transformation of the first descriptor (DESCR_1) into a library of preconfigured messages (MES_H) defining a given reference (REF_H); ▪ An instantiation of a message (MES_H) of the reference (REF_H) to generate a data set on a memory (M).