Application Service Energy Consumption Calculation in Wireless Networks
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Solution Overview
Problem
Mobile network operators face challenges in determining the expected energy consumption for their networks and the impact on connected devices when deploying new communication services or slices to meet application service requirements.
Innovation Solution
A method and apparatus for calculating application service energy consumption in a wireless communication network, involving receiving an energy data requirement, determining energy data producers, collecting and computing energy data, and sending a report to the requesting node, utilizing at least one network node with a receiver, processor, and transmitter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If energy data collection and computation is implemented for application services, then energy consumption assessment capability is improved, but system complexity increases
Solution Approach 1:
The system segments energy data collection by identifying specific energy data producers (gNBs, UPFs, application servers) associated with application services. Each network node collects and reports energy data independently, dividing the complex measurement task into manageable segments that can be processed separately and aggregated to provide comprehensive energy consumption assessment.
2Measurement precision
If comprehensive energy data is collected from multiple producers, then energy measurement accuracy is improved, but data collection complexity increases
Solution Approach 1:
The system introduces an intermediary mechanism where application functions request energy data from data management functions, which then coordinate with energy data producers. This intermediary layer simplifies the data collection process by providing a standardized interface and workflow, reducing the complexity that would otherwise arise from direct multi-node data gathering.
3Productivity
If energy consumption monitoring is implemented for network slices, then energy efficiency management is improved, but operational complexity increases
Solution Approach 1:
The system implements feedback mechanisms where energy consumption data is continuously collected from network slices and application services, processed by data management functions, and reported back to application functions and network operators. This feedback loop enables automated energy efficiency optimization and simplifies operations by providing actionable insights without requiring manual monitoring of complex multi-node systems.
Data Source
AI summary
There is provided a method for providing energy data for an application service. The method comprises receiving an energy data requirement for the application service from a requesting node, and determining a set of energy data producers associated with the application service from which to collect energy data based on the energy data requirement. The method further comprises collecting a first set of energy data from the set of energy data producers, and computing a second set of energy data for the application service based on the first set of energy data. The method 400 further comprises sending a report comprising the second set of energy data to the requesting node.