Dynamic Network Speed Control via Power Reallocation
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Solution Overview
Problem
Existing information handling systems lack efficient dynamic control of network speeds, leading to suboptimal power consumption and user experience, especially in mobile devices with varying network requirements.
Innovation Solution
An information handling system that builds a performance model based on key performance indicators, predicts network bandwidth requirements, adjusts power consumption accordingly, and reallocates saved power to other system components, using artificial intelligence and machine learning for dynamic optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If network speed is increased to meet varying network requirements, then user experience and application performance are improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts network speed based on real-time performance monitoring and prediction. The network interface controller changes operational states (speed levels) according to actual bandwidth requirements, transitioning between high and low speed states to match application demands while optimizing power consumption.
Solution Approach 2:
The system changes the operational parameters of the network interface controller, specifically adjusting the network speed parameter based on predicted bandwidth requirements. By modifying this parameter dynamically, the system achieves optimal balance between performance and power consumption.
2Use of energy by moving object
If network speed is decreased to reduce power consumption, then power efficiency is improved, but user experience and application performance deteriorate
Solution Approach 1:
The system implements a feedback mechanism where network performance is continuously monitored using key performance indicators. This feedback information is fed into a machine learning model that predicts future bandwidth requirements, which then guides network speed adjustment decisions to maintain user experience while optimizing power consumption.
Solution Approach 2:
The system performs preliminary actions by predicting future network bandwidth requirements before actual network operations occur. The machine learning model anticipates upcoming bandwidth needs based on historical patterns and current state, allowing the system to proactively adjust network speed to prevent performance degradation.
3Ease of operation
If fixed network speed is maintained to ensure consistent performance, then user experience is preserved, but power consumption is suboptimal
Solution Approach 1:
The system transitions from a static fixed network speed approach to a dynamic adjustment mechanism. The network interface controller adapts its speed based on actual application demands, being fast when needed and slow when not needed, thereby eliminating wasted energy while preserving user experience through intelligent adaptability.
Data Source
AI summary
An information handling system builds a performance model for a network based on key performance indicators, and evaluates performance of applications using the key performance indicators according to useability metrics. The system predicts network bandwidth requirement based on the performance model for the network and the performance of the applications, adjusts power consumption of the network based on the predicted network bandwidth requirement, and reallocates power saved from the adjusting of the power consumption of the network to a component of the information handling system.