Latency-Based Energy Storage Selection for Mobile Devices

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Solution Overview

Problem

Mobile computing devices face challenges in balancing power management to extend battery life while maintaining performance, as existing strategies often compromise between processor performance and battery efficiency, leading to user dissatisfaction.

Innovation Solution

The implementation of a latency-based energy storage device selection system that predicts latency behavior and adjusts power supply by favoring high power density devices for latency-sensitive tasks and high energy density devices for non-latency sensitive tasks, using a combination of heterogeneous energy storage devices and setting power ratios to optimize power draw.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Duration of action of stationary object

If power management strategies control processor and battery utilization to extend battery life, then battery life is improved, but device performance deteriorates

Engineering Contradiction:
Improvebattery lifeVSAvoiddevice performance
Core Design Contradiction:
Duration of action of stationary objectVSProductivity

Solution Approach 1:

The patent segments the power supply function by dividing it into multiple heterogeneous energy storage devices (e.g., high power density devices and high energy density devices). Each device type is optimized for specific task categories: high power density devices handle latency-sensitive tasks while high energy density devices handle non-latency-sensitive tasks. This segmentation allows the system to simultaneously optimize for both performance (when needed) and battery life (when possible), resolving the contradiction between extending battery life and maintaining device performance.

Inventive Principle:
Principle #1Segmentation

2Speed

If high power density devices are used for latency sensitive tasks, then device performance is improved, but energy consumption increases

Engineering Contradiction:
Improveresponse timeVSAvoidenergy consumption
Core Design Contradiction:
SpeedVSUse of energy by moving object

Solution Approach 1:

The patent applies local quality by matching specific device characteristics to specific task requirements. High power density devices are selectively deployed only for latency-sensitive tasks where fast response is critical, while high energy density devices are used for non-latency-sensitive tasks. This localized application of device qualities ensures that high energy consumption is incurred only when absolutely necessary for performance, rather than continuously, thus resolving the contradiction between improving response time and reducing energy consumption.

Inventive Principle:
Principle #3Local quality

3Adaptability or versatility

If multiple heterogeneous energy storage devices are used, then system versatility is improved, but device complexity increases

Engineering Contradiction:
Improvesystem versatilityVSAvoidsystem complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements dynamics by introducing a power manager that dynamically selects and switches between different energy storage devices based on real-time task characteristics and system state. The system adapts its configuration on-the-fly, choosing high power density devices for latency-sensitive tasks and high energy density devices for other tasks. This dynamic adaptation provides system versatility without requiring manual reconfiguration, and the automated power management logic handles the complexity internally, resolving the contradiction between improving system versatility and managing device complexity.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentUS9939862B2Latency-based energy storage device selection
Publication Date: 2018.04.10 MICROSOFT TECHNOLOGY LICENSING LLC
  • US9939862B2 patent drawing
  • US9939862B2 patent drawing
  • US9939862B2 patent drawing

AI summary

Latency-based selections of energy storage devices are described herein. In implementations, latency behavior of computing tasks performed by a computing device is predicted for a period of time. Based on the predicted latency behavior of the computing device over the period of time, an assessment is made regarding which of multiple heterogeneous energy storage devices are most appropriate to service the system workload. For example, high energy density devices may be favored for latency sensitive tasks whereas high energy density devices may be favored when latency sensitivity is not a concern. A combination of energy storage devices to service the current workload is selected based upon the latency considerations and then power supply settings are adjusted to cause supply of power from the selected combination of energy storage devices during the time period.