Orchestrator-Based Data Acquisition for AI Network Automation
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Solution Overview
Problem
Networks lack the ability to acquire data and cooperate with an artificial intelligence management plane when big data and AI technologies are introduced, leading to inefficiencies and inflexibilities in network operation and maintenance.
Innovation Solution
A data acquisition request method is established where an orchestrator generates and sends a data acquisition request message to a network control device or target network node, enabling data acquisition and processing through an AI platform, allowing for automation, intellectualization, and closed-loop control within the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual analysis processing mode is used, then operational simplicity is maintained, but processing efficiency is low and cost is high
Solution Approach 1:
The patent introduces an orchestrator as an intermediary component that bridges the network side and the artificial intelligence management plane. The orchestrator receives data acquisition requests from AI applications, translates them into network-specific protocols, and manages the coordination between different system components, thereby enabling efficient automated processing without requiring direct complex integration between all elements.
Solution Approach 2:
The system is divided into distinct functional modules: the orchestrator for request management, the network side for data collection, and the artificial intelligence management plane for processing. This segmentation allows each component to specialize in specific tasks, improving overall processing efficiency while maintaining manageable complexity through clear interface definitions.
2Adaptability or versatility
If rule-based automatic processing mode is used, then operational cost is reduced, but application range is narrow and flexibility is low
Solution Approach 1:
The system replaces static rule-based processing with dynamic AI-driven processing. The artificial intelligence management plane can adapt to different data types, processing requirements, and business scenarios by learning from data patterns and making intelligent decisions, thereby achieving high flexibility without requiring complex rule configurations for each scenario.
Solution Approach 2:
The system changes the fundamental parameter of processing methodology from fixed rules to adaptive AI algorithms. This allows the processing behavior to dynamically adjust based on input data characteristics and operational context, providing versatility across different application scenarios while the orchestrator manages the complexity of parameter adjustments.
3Productivity
If network automation is implemented, then operational efficiency is improved, but network architecture complexity increases
Solution Approach 1:
The orchestrator serves as a mediating layer that abstracts the complexity of network automation. It handles the coordination between AI applications and network elements, managing data acquisition requests and responses without requiring direct complex interactions between all components, thereby improving operational efficiency while containing architecture complexity through interface abstraction.
Solution Approach 2:
The orchestrator is designed as a universal component that can handle multiple types of data acquisition requests from different AI applications and communicate with various network elements. This multi-functionality consolidates automation capabilities in a single component, improving operational efficiency across diverse scenarios while avoiding the need for separate complex automation systems for each application.
Data Source
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AI summary
A data processing method and device, a storage medium and an electronic device are disclosed. The method comprises responsive to determining that an application instance is established, generating, by an orchestrator, a data acquisition request message corresponding to the application instance and sending the data acquisition request message to a next communication node, wherein the next communication node includes one of a network control device and a target network node; acquiring, by the target network node, data according to the data acquisition request message received from the orchestrator or through the network control device, and sending a data acquisition result to a processing device of the application instance; and processing, by the processing device of the application instance, the data acquisition result through a model in the application instance and outputting a processing result.