Intent Translation Microservice for TOSCA-Based Network Orchestration
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Solution Overview
Problem
There is a need for a standardized method to translate intents defined in various standards into a common TOSCA-based model for intent-based network management and orchestration, as different standards lack consensus on intent representation and implementation.
Innovation Solution
A microservice within a service and network orchestrator receives an intent defined in a first format associated with a specific standard and translates it into a TOSCA-based format, enabling interoperability and seamless communication across different intent formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple intent models from different standards are used, then diverse intent representation capabilities are improved, but system complexity and translation difficulty increase
Solution Approach 1:
The patent introduces a translation service as an intermediary component that mediates between multiple intent models from different standards and the core orchestrator. This translation service converts intents from various standards (ETSI ZSM, TMF, 3GPP) into a unified internal representation, allowing the system to support diverse intent representations without increasing core system complexity. The translation service acts as a buffer layer that handles the complexity of multiple standards externally.
Solution Approach 2:
The patent creates a universal intent representation model that can handle multiple intent formats through a common structure. The unified intent model includes standardized fields for service identification, resource requirements, quality of service parameters, and operational constraints that can represent intents from different standards. This universal model allows the orchestrator to process diverse intents through a single processing path, maintaining system simplicity while supporting versatility.
2Manufacturing precision
If manual configuration management methods are used, then implementation precision is improved, but labor intensity and time consumption increase
Solution Approach 1:
The patent implements automated intent-based orchestration where the system self-configures network resources based on high-level intent descriptions from users. The orchestrator automatically translates business intents into technical configurations, allocates resources, and enforces policies without manual intervention. This automation maintains configuration precision through structured intent models and validation rules while eliminating the time-consuming manual configuration process.
Solution Approach 2:
The patent employs templates and pre-defined intent models that capture common network configuration patterns. These templates include pre-configured resource requirements, quality of service parameters, and operational constraints for typical services. By using these pre-prepared templates, the system can rapidly instantiate configurations with high precision without requiring manual setup for each new service, significantly reducing time consumption while maintaining accuracy.
3Adaptability or versatility
If standardized intent translation to TOSCA is implemented, then interoperability is improved, but translation complexity increases
Solution Approach 1:
The patent introduces a translation service as an intermediary component that mediates between multiple intent models from different standards and the core orchestrator. This translation service converts intents from various standards (ETSI ZSM, TMF, 3GPP) into a unified internal representation, allowing the system to support diverse intent representations without increasing core system complexity. The translation service acts as a buffer layer that handles the complexity of multiple standards externally.
Solution Approach 2:
The patent employs parameter mapping and transformation techniques to convert between different intent model parameters and the unified TOSCA-based representation. The system maintains parameter mapping tables that define correspondences between standards-specific parameters and universal parameters. By changing parameters through standardized mapping rules rather than restructuring entire models, the translation process becomes more manageable and less complex.
Data Source
AI summary
As described herein, a system, method, and computer program are provided for intent translation to Topology and Orchestration Specification for Cloud Applications (TOSCA) in intent-based orchestration. A microservice of a service and network orchestrator receives an intent defined in a first format associated with a first standard used for modeling and management of network services. The microservice translates the intent defined in the first format to a second format associated with a TOSCA-based model used for modeling and management of network services, to form the intent defined in the second format. The microservice outputs the intent defined in the second format.