Power Control Module for Dynamic Network Node Energy Optimization
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Solution Overview
Problem
Existing power control methods in communication networks lack flexibility to dynamically adjust power consumption according to real-time and dynamic traffic load requirements, leading to inefficient energy usage.
Innovation Solution
A method involving a power control module that receives operational state information from network nodes to generate power control recommendations, allowing for flexible optimization of power consumption by considering the state of services, software, and hardware, and enabling full or partial power control adjustments based on current and predicted operational states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If power control commands are strictly followed at the network node, then power consumption is reduced, but flexibility to adapt to real-time traffic load requirements is lost
Solution Approach 1:
The power control system transitions from static commands to dynamic recommendations that are continuously adapted based on real-time operational state information. The power control module generates recommendations that dynamically adjust to changing traffic conditions, service states, and hardware conditions, allowing the network node to flexibly optimize power consumption without rigid constraints.
Solution Approach 2:
The system changes the parameter of power control from fixed commands to variable recommendations based on multiple parameters including operational state information, traffic load characteristics, service requirements, and hardware conditions. This allows power consumption optimization to adapt to different operating scenarios through parameter-driven flexibility.
2Adaptability or versatility
If power control recommendations consider multiple operational states (services, software, hardware), then flexibility and optimization are improved, but system complexity increases
Solution Approach 1:
The operational state is segmented into distinct categories: service level states, software module states, and hardware unit states. Each segment can be independently monitored and evaluated, allowing the power control module to process complex operational information in a structured manner without overwhelming complexity.
Solution Approach 2:
The power control module serves multiple functions by evaluating different types of operational state information (services, software, hardware) and generating comprehensive power control recommendations. This multi-functional approach consolidates complexity into a single module that handles diverse operational aspects through unified processing.
3Loss of energy
If full power control recommendations are generated covering all parameters, then power consumption optimization is maximized, but computational complexity increases
Solution Approach 1:
The system allows for partial power control recommendations that cover only the most relevant parameters for current operational conditions. This enables the power control module to generate sufficient recommendations for effective power optimization without the computational burden of analyzing all possible parameters, achieving adequate action with reduced complexity.
Data Source
AI summary
The present invention relates to power control optimization in a communication network aiming at increased flexibility for controlling the power consumption in a network node (10). The network node (10) forwards operational state information to a power control module (18). The power control module (18) generates a power control recommendation as a proposal for the power control configuration of the network node (10) to optimize power consumption thereof. The power control recommendation is then forwarded to the network node (10) for subsequent optimization of the controlling of power consumption in the network node (10).