5G Service Energy Evaluation for Split Network Functions
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Solution Overview
Problem
The existing energy efficiency evaluation methods for network elements in 4G networks are not applicable in the service-based architecture of 5G networks, as the functions of network elements in 4G are split, leading to a need for a new approach to evaluate energy efficiency in 5G networks.
Innovation Solution
A method and device for energy efficiency evaluation in a service-based architecture, where a service producer obtains service energy consumption data, including service information and energy consumption information, to determine energy efficiency information for target objects, such as network elements split in 5G networks, considering service feature requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network element functions are split in service-based architecture, then adaptability to 5G network is improved, but energy efficiency evaluation capability deteriorates
Solution Approach 1:
The patent introduces an energy efficiency evaluation function as an intermediary component that collects energy consumption data from multiple split network elements and performs centralized evaluation. This mediator aggregates data from different service instances and calculates overall energy efficiency metrics, resolving the evaluation capability loss caused by function splitting.
Solution Approach 2:
The energy efficiency evaluation function is designed with multi-functionality to handle various service types and network elements simultaneously. It can evaluate energy efficiency for different service instances, time periods, and performance metrics, making it universally applicable across the split network architecture while maintaining comprehensive evaluation capability.
2Adaptability or versatility
If service-based architecture is used, then service flexibility is improved, but complexity of energy efficiency evaluation increases
Solution Approach 1:
The patent segments the energy efficiency evaluation process into distinct functional modules: data collection from service instances, data preprocessing, evaluation calculation, and result reporting. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while supporting service flexibility.
Solution Approach 2:
The system implements feedback mechanisms where energy efficiency evaluation results are fed back to network management and service instances. This feedback loop enables dynamic optimization of energy consumption based on evaluation outcomes, managing complexity through iterative improvement rather than complex upfront design.
3Measurement precision
If energy efficiency evaluation is performed for split functions, then evaluation accuracy for specific services is improved, but data collection complexity increases
Solution Approach 1:
The patent implements preliminary action by having service instances pre-collect and report their energy consumption data to the evaluation function at regular intervals or upon service completion. This preliminary data preparation reduces the complexity of real-time data collection during evaluation, while maintaining accurate service-specific measurements.
Data Source
AI summary
One example energy efficiency evaluation method comprises obtaining, by a service producer, service energy consumption data of the target object, where the service energy consumption data includes service information and energy consumption information of the target object. The service producer can then determine energy efficiency information of the target object based on the service energy consumption data.