Shared Hierarchical Data Model for Distributed Data Consistency
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Solution Overview
Problem
Distributed computing systems face inefficiencies and errors due to non-uniform data structures across components, leading to cumbersome upgrades and prolonged development lifecycles, as well as issues in network monitoring and data analytics.
Innovation Solution
Implementing a shared hierarchical data design model that provides a common data structure inventory and verification tools to ensure data uniformity across components, allowing systems to access and conform to a unified data design model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If independent developers design and create data structures independently in distributed systems, then each component can be developed autonomously, but data non-uniformity causes errors and inefficiencies across the system
Solution Approach 1:
The patent implements a universal data design model that serves multiple components across the distributed system. This model defines standardized data structures, schemas, and relationships that can be reused by all developers, ensuring data consistency while allowing independent development. The model acts as a common framework that maintains reliability across autonomous components.
2Ease of operation
If non-uniform data structures are transferred between components, then components can operate independently with different data designs, but data formatting and integration techniques are required causing errors and inefficiencies
Solution Approach 1:
The patent enforces homogeneous data structures across all components by requiring them to conform to the universal data design model. This eliminates the need for complex data formatting and integration techniques during transfers, as all components use the same standardized schemas and data formats, thereby improving transfer efficiency while maintaining independent operation capability.
3Stability of the object's composition
If legacy systems use non-uniform data designs, then existing systems can maintain their current architecture, but upgrades become cumbersome and time-consuming
Solution Approach 1:
The patent implements preliminary action by establishing the universal data design model before upgrades are needed. This model provides a standardized target architecture that legacy systems can progressively migrate to. By having the target model predefined, upgrades become more systematic and less cumbersome, reducing the time required for modernization while maintaining stability during the transition.
4Adaptability or versatility
If data structures lack uniformity across distributed systems, then components can be developed with different requirements, but network monitoring and data analytics components experience errors and inefficiencies
Solution Approach 1:
The universal data design model provides standardized schemas and data structures that enable network monitoring and data analytics components to operate efficiently. By ensuring all components use the same data formats and relationships, the model allows monitoring tools to accurately measure and analyze data across the entire distributed system without errors caused by non-uniformity.
Data Source
AI summary
Various techniques described herein relate to using a shared hierarchical data design model for creating and transferring data within distributed systems. Components within a distributed system may access a shared hierarchical data design model when designing and creating software components, data structures, or application programming interfaces (APIs) through which data is transferred. Additional techniques include verifying and enforcing that the components of the distributed system conform with the shared hierarchical data design model, including using design/development environments and element-by-element analyses of the data structures transferred between components of the distributed system.