Demand-Based Access Point Power Optimization
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Solution Overview
Problem
Dynamic network environments with varying device and application demands pose challenges for wireless network optimization, leading to poor performance, energy inefficiency, and increased maintenance costs due to always-on access points.
Innovation Solution
Implementing demand-based optimization logic to adjust the output power of access points based on network demands, using data from client devices and environmental sources to generate power configurations that optimize energy usage while maintaining service levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If access points are kept in an always-on state to maintain network availability, then network reliability is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts access point power states based on real-time network demand conditions. Access points transition between active, standby, and powered-off states according to monitored parameters such as client device presence, traffic load, and service level agreement requirements, resolving the contradiction between continuous availability and energy consumption
Solution Approach 2:
The system performs preliminary assessment of network demand conditions before transitioning access points to different power states. By monitoring predictive indicators and current load conditions in advance, the system ensures that access points are activated or deactivated at optimal times to maintain reliability while minimizing energy consumption
2Area of stationary object
If access points operate continuously on all frequency bands to ensure coverage, then network coverage is improved, but energy consumption increases
Solution Approach 1:
The system segments the wireless network into multiple independent access points, each capable of operating on different frequency bands. This allows selective activation of specific access points and frequency bands based on local demand conditions, maintaining adequate coverage while reducing overall energy consumption by avoiding continuous operation of all bands
Solution Approach 2:
The system applies different power states and frequency band configurations to different access points based on local network demand conditions. Each access point is independently optimized according to its specific environment, client distribution, and traffic patterns, allowing coverage to be maintained in high-demand areas while reducing power consumption in low-demand areas
3Use of energy by moving object
If access points are turned off during non-working hours to save energy, then energy consumption is reduced, but network reliability deteriorates
Solution Approach 1:
The system continuously monitors network demand conditions, client device presence, and service level agreement compliance as feedback signals. This real-time feedback enables dynamic adjustment of access point power states, ensuring that access points remain active when needed to maintain reliability and are deactivated when demand is low, thereby resolving the contradiction between energy savings and network availability
4Use of energy by moving object
If demand-based power adjustment is implemented to reduce energy consumption, then energy efficiency is improved, but system complexity increases
Solution Approach 1:
The system implements self-service mechanisms where access points automatically monitor their own operational conditions, assess network demand, and transition to appropriate power states without requiring complex centralized control. Each access point independently evaluates its own workload, client presence, and environmental conditions, reducing overall system complexity while maintaining energy efficiency
Data Source
AI summary
Various methods, systems, and/or processes are described herein that rely on a demand-based optimization logic that aims to improve wireless network performance. It involves selecting a floorplan, identifying access points associated with the floorplan, and assessing network demands of client devices within the area. Based on the demands, a demand-based power configuration is generated to adjust the output power of one or more access points. This configuration is transmitted to the identified access points to optimize network performance. By adjusting the power of access points to match the needs of client devices, more efficient and effective wireless network usage is realized.