Wireless Wake-Up Scheduling for Lower Edge Device Power Use
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Solution Overview
Problem
Existing wireless devices face challenges in optimizing power consumption while maintaining reliable wireless communication, as network settings are often set statically without considering the specific characteristics of wireless access points, leading to unnecessary energy consumption and reduced battery life.
Innovation Solution
The edge device dynamically adjusts settings such as wake-up intervals, ignores certain beacons, and reduces transmit power based on learned settings and environmental characteristics using machine learning to optimize power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network settings are set statically to ensure capability with a wide range of wireless access points, then compatibility is improved, but power consumption increases
Solution Approach 1:
The patent transforms static network settings into dynamic settings that automatically adapt based on the detected wireless access point characteristics. The edge device learns AP-specific parameters (beacon intervals, DTIM periods, etc.) and adjusts its wake-up schedule dynamically, allowing optimal power consumption for each specific AP while maintaining compatibility across different vendors and models.
Solution Approach 2:
The system changes operational parameters (wake-up intervals, power transmission levels) based on learned characteristics of the connected access point. By modifying these parameters dynamically rather than using fixed values, the device achieves both compatibility with various APs and optimized power consumption tailored to each specific AP's behavior patterns.
2Use of energy by moving object
If network settings are set statically to maintain acceptable battery life, then power consumption is controlled, but compatibility with wide range of wireless access points deteriorates
Solution Approach 1:
The edge device performs self-configuration by automatically learning the characteristics of the connected access point and adjusting its own network settings accordingly. This self-service approach eliminates the need for manual configuration or vendor-specific settings, enabling the device to work with any AP while optimizing power consumption automatically.
Solution Approach 2:
The system implements a feedback loop where the device monitors AP beacon transmissions and other network traffic, learns from these observations, and adjusts its wake-up schedule based on the detected patterns. This continuous feedback mechanism ensures both compatibility with diverse APs and optimized power consumption adapted to each specific network environment.
3Duration of action of stationary object
If device wake-up schedule is adjusted to reduce power consumption, then battery life is extended, but reliable communication with wireless access point may be compromised
Solution Approach 1:
The device performs preliminary learning of the access point's transmission patterns before finalizing its wake-up schedule. By analyzing beacon intervals, DTIM periods, and other AP-specific characteristics in advance, the system can confidently set longer wake-up intervals that extend battery life while ensuring the device is always awake at the right moments to maintain reliable communication.
Data Source
AI summary
A method of reducing a power consumption of wireless communication circuitry of an edge device according to one embodiment includes determining a delivery traffic indication map (DTIM) interval of a wireless access point communicatively coupled to the edge device via the wireless communication circuitry of the edge device and adjusting a wake-up interval of the wireless communication circuitry of the edge device based on the DTIM interval to reduce the power consumption of the wireless communication circuitry of the edge device.