Mobile Station Battery Life Extension via Dynamic Resource Allocation
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Solution Overview
Problem
Mobile stations experience reduced battery life due to increased resource allocation for applications, leading to unexpected depletion of battery power when needed most, as users lack control over resource management parameters like RF-transmit power and data-synchronization frequencies.
Innovation Solution
A method in a mobile station that determines its location and destination, estimates travel time and remaining battery power, and reduces resource allocation to extend battery life, ensuring at least 25% power remains upon arrival, by adjusting processor execution cycles, RF-transmit power, and data-synchronization frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resource allocation is increased to support application execution, then application functionality is improved, but battery life is reduced
Solution Approach 1:
The system dynamically adjusts resource allocation parameters (processor execution cycles, RF-transmit power, data-synchronization frequency) based on real-time conditions including estimated time to destination and current battery power levels. This allows the mobile station to adapt resource allocation to changing operational requirements while maintaining application functionality and extending battery life.
Solution Approach 2:
The system changes key operational parameters (execution cycles, transmit power, synchronization frequency) based on calculated battery consumption rates and estimated time to destination. By adjusting these parameters dynamically, the system optimizes the balance between application performance and battery conservation.
2Reliability
If data-synchronization frequency is increased for real-time access, then data availability is improved, but battery power consumption increases
Solution Approach 1:
The data-synchronization frequency is dynamically adjusted based on the estimated time to destination and current battery power level. The system calculates an optimal synchronization frequency that maintains data availability while consuming less battery power, particularly when the destination is far away or battery power is low.
3Reliability
If RF-transmit power is increased for better communication quality, then communication reliability is improved, but battery power consumption increases
Solution Approach 1:
The RF-transmit power is adjusted as a controllable parameter based on the estimated time to destination and battery power level. The system modifies transmit power to achieve adequate communication reliability while minimizing battery consumption, particularly during long trips or when battery power is low.
4Productivity
If processor execution cycles are increased for complex applications, then application performance is improved, but battery power consumption increases
Solution Approach 1:
The number of processor execution cycles allocated to applications is dynamically adjusted based on the estimated time to destination and current battery power level. The system provides sufficient processing power for application execution while conserving battery energy, particularly when the destination is far away or battery power is low.
Data Source
AI summary
A method and system for reducing resource consumption to extend battery life based on an estimated time to a destination location is provided. A mobile station having mobile station resources, and having a battery that provides power to the mobile station resources for executing applications, is located at a current location and is heading to a destination location. The mobile station allocates a first extent of the resources for execution of at least one application by the mobile station. The mobile station estimates a current travel time from the current location to reach the destination location, and estimates a current remaining power of the battery. Based on the estimated remaining power and the estimated travel time to reach the destination, the mobile station reduces the allocation of resources for execution of the at least one application from the first extent to a second extent.