Orchestrated Distributed Network for Multi-Type Interaction Data
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Solution Overview
Problem
Complex network environments face challenges in managing, analyzing, and processing vast volumes of interaction data from diverse sources, with issues related to data volume, velocity, and variety, necessitating efficient and timely data processing and analysis.
Innovation Solution
A distribution computer network with specialized computing and orchestrative computing is employed, utilizing advanced data integration techniques and flexible data models to integrate and harmonize disparate data types, with an orchestration node coordinating task-oriented nodes to execute tasks and manage a rules database for dynamic operation changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If specialized computing is used to process different data types, then data processing efficiency is improved, but system complexity increases due to multiple nodes with distinct parameters
Solution Approach 1:
The system divides computing nodes into specialized nodes for different data types (first specialized nodes for first data type, second specialized nodes for second data type) and introduces separate orchestration nodes. This segmentation allows each node type to be optimized for its specific data processing task, improving overall efficiency while managing complexity through modular architecture.
Solution Approach 2:
Multiple orchestration nodes are introduced that can coordinate different combinations of specialized nodes. The orchestration nodes serve universal functions by receiving tasks, extracting parameters, and coordinating appropriate specialized nodes, making the system flexible and adaptable to various data processing requirements without requiring custom specialized nodes for each scenario.
2Adaptability or versatility
If multiple orchestration nodes are introduced to coordinate specialized nodes, then task execution flexibility is improved, but control complexity increases
Solution Approach 1:
The control function is segmented into multiple independent orchestration nodes, each capable of coordinating specialized nodes. This segmentation distributes control complexity across multiple nodes rather than concentrating it in a single complex controller, enabling flexible task execution while managing control complexity through modular design.
Solution Approach 2:
The system extracts task parameters from instruction data and uses these parameters to dynamically configure and coordinate specialized nodes. By changing parameters based on extracted task information, the system achieves flexible task execution without requiring complex hard-coded control logic, thereby reducing control complexity.
3Quantity of substance
If data from diverse sources is integrated, then data comprehensiveness is improved, but data processing complexity increases due to varying data formats
Solution Approach 1:
Specialized nodes are created for different data types, each with specific processing parameters optimized for its data format. This local quality approach allows each node to handle its specific data type efficiently while the orchestration layer manages the diversity, reducing overall processing complexity through specialization.
Solution Approach 2:
Orchestration nodes act as intermediaries between diverse data sources and specialized processing nodes. They extract parameters from instruction data and coordinate appropriate specialized nodes, serving as a mediator that manages data format variations and simplifies the data processing architecture while maintaining comprehensive data integration.
Data Source
AI summary
A distribution computer network is disclosed. The distribution computer network includes a plurality of computer nodes, each configured to run a set of softwares with distinct data processing parameters, wherein at least one of the computer nodes being configured as an orchestration node and the remaining computer nodes being configured as task-oriented nodes, the orchestration node being configured, upon receiving instruction data to perform a task, and based on a set of extracted task parameters, to coordinate operation of the remaining computer nodes in the distribution network to execute the task. The distribution computer network may further include a rules database accessible by the computer nodes, the rules database comprising rules modifiable by the orchestration node to direct changes in the operation of at least one of the task-oriented nodes based on the task.