Wireless Scheduling Based on Battery Life
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional wireless communication systems do not consider battery life when scheduling wake and sleep intervals for battery-powered devices, leading to unnecessary power consumption and reduced operational time.
Innovation Solution
Implementing a method where communication devices dynamically adjust their wake and sleep timing based on their battery life by transmitting power status information to a central network device, which then reschedules TWT sessions to prioritize devices with lower battery life, thereby extending the operational time of the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If conventional wireless communication systems schedule wake and sleep intervals without considering battery life, then communication scheduling is simple and uniform, but battery-powered devices experience unnecessary power consumption and reduced operational time
Solution Approach 1:
The system dynamically changes scheduling parameters (wake intervals, communication timing) based on the battery life parameter of each device. Devices with lower battery life receive adjusted scheduling parameters that reduce their power consumption, while devices with higher battery life maintain or increase their communication activity. This parameter adaptation resolves the contradiction by making operational time and power consumption dependent on the battery status parameter.
Solution Approach 2:
The communication schedule transitions from a static, uniform schedule to a dynamic schedule that adapts to each device's battery life status. The access point continuously monitors battery life reports from devices and adjusts wake intervals and communication opportunities accordingly. This dynamic adjustment ensures that devices with limited battery life automatically receive more conservative scheduling, extending their operational time without manual intervention.
2Duration of action of moving object
If the system prioritizes devices with lower battery life in communication scheduling, then battery depletion is slowed and operational time is extended, but the scheduling complexity increases
Solution Approach 1:
Devices report their battery life status to the access point in advance, allowing the system to proactively adjust scheduling before battery depletion becomes critical. The access point maintains a table of battery life information for each device and uses this pre-collected data to make scheduling decisions. This preliminary action approach reduces the need for complex real-time calculations and enables simpler, more efficient scheduling algorithms.
Solution Approach 2:
The system implements a feedback mechanism where devices periodically report their battery life status to the access point, which then adjusts the communication schedule based on this feedback. The access point uses the reported battery life information to determine appropriate wake intervals and communication opportunities for each device. This feedback loop simplifies the scheduling complexity by providing the system with up-to-date device status information, enabling rule-based scheduling decisions rather than requiring complex optimization algorithms.
Data Source
AI summary
A method includes comparing a first battery life value of a first wireless device with a second battery life value of a second wireless device, and in response to determining, based on the comparing, that the first battery life value is less than the second battery life, adjusting a communication schedule so a duration of awake state operation of the first wireless device is less than a duration of awake state operation of the second wireless device.