Conditional Schema Payload Restructuring for Efficient Transmission
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Solution Overview
Problem
Existing systems inefficiently handle structured payloads of varying sizes due to fixed schemas, leading to increased storage, bandwidth, and processing requirements, and are prone to inoperability and costly updates with multiple schema variants.
Innovation Solution
Implement an enhanced schema specifying contingently-required fields with conditions, allowing iterative restructuring to ensure payloads include necessary data while minimizing size, using a single schema to manage variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed schema is used for all structured payloads, then schema validation is simple, but payload size cannot be optimized and storage/bandwidth requirements increase
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed schema to a dynamic schema that automatically adapts to payload contents. The system evaluates conditions within the schema (such as field values or relationships) to dynamically determine which fields are required, allowing the schema to change its requirements based on the actual data being transmitted. This resolves the contradiction by maintaining simple validation logic while enabling payload size optimization through conditional field inclusion.
Solution Approach 2:
The patent changes the parameters of the schema from static to dynamic by introducing conditional logic that modifies schema requirements based on payload characteristics. The system evaluates conditions (such as data types, field values, or relationships) and adjusts the schema's field requirements accordingly. This allows the same schema to produce different validation rules for different payloads, optimizing both validation simplicity and payload efficiency.
2Quantity of substance
If multiple schema variants are used to handle different payload structures, then payload optimization is achieved, but system complexity and update costs increase
Solution Approach 1:
The patent applies universality by creating a single schema that can handle multiple payload structures through embedded conditional logic. Instead of maintaining separate schema variants for different scenarios, the unified schema uses conditions to automatically select appropriate field requirements. This single multi-functional schema reduces system complexity while achieving the same payload optimization that would otherwise require multiple specialized schemas.
Solution Approach 2:
The patent merges multiple schema variants into a single unified schema by combining their conditional logic and field requirements into one comprehensive structure. The merged schema integrates the validation rules from what would have been separate schemas, eliminating the need to maintain and update multiple variants. This reduces system complexity while preserving the ability to optimize payload sizes for different scenarios.
3Reliability
If all fields are always included in payloads, then data completeness is ensured, but transmission efficiency decreases due to unnecessary data
Solution Approach 1:
The patent applies local quality by making field requirements conditional rather than uniform. Instead of always including all fields, the system evaluates local conditions (such as specific field values or data relationships) to determine which fields are actually needed for each payload. This ensures data completeness for required fields while eliminating unnecessary fields, thereby improving transmission efficiency without sacrificing reliability.
Solution Approach 2:
The patent applies partial action by including only the necessary fields in each payload rather than all possible fields. The schema conditions evaluate what is minimally required for valid data exchange, and the system includes only those fields. This partial approach ensures data completeness for the purposes at hand while avoiding the excessive data transmission that would occur if all fields were always included, thus improving transmission efficiency.
Data Source
AI summary
Disclosed herein is a computer system and method for restructuring a structured payload for efficient downstream storage, transmission, and processing, in which a schema specifies fields including at least one contingently-required field. At least one processor is configured to: retrieve the schema and the structured payload from processor-readable memory; evaluate, for each contingently-required field in the schema, whether a respective condition in the schema is either satisfied or unsatisfied by content in the structured payload; responsive to a respective condition being satisfied, add the contingently-required field to a list of required fields; responsive to a respective condition being unsatisfied, add the contingently-required field to a list of removed fields; and generate a restructured payload by: adding to the structured payload all fields in the list of required fields that are missing; and removing from the structured payload all fields in the list of removed fields that are present.


