Power Pattern Analysis for Embedded Device Optimization
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Solution Overview
Problem
Embedded devices, particularly those used in IoT systems, face challenges in optimizing power consumption due to their reliance on battery power, where existing techniques often rely on static power measurements that do not effectively address power fluctuations, leading to inefficient battery life in complex systems where device replacement is not feasible.
Innovation Solution
A system and method that includes a processor and memory modules for monitoring, generating, matching, and identifying power patterns based on voltage changes to detect peak power consumption functions, generating recommendations for code changes to optimize power usage, thereby reducing peak power fluctuations and extending battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static power measurements are used to optimize power consumption, then the optimization process is simple, but the optimization effectiveness is insufficient and does not provide desired outcomes
Solution Approach 1:
The patent transitions from static power measurements to dynamic power pattern analysis. The system continuously monitors power consumption and identifies temporal patterns (recurring power spikes) that indicate problematic code sections. This dynamic approach allows the system to adapt to varying operational conditions and provide more effective optimization recommendations while maintaining reasonable complexity through automated pattern recognition.
Solution Approach 2:
The system implements feedback by measuring actual power consumption, comparing it against identified patterns, and generating recommendations based on the correlation between code execution and power spikes. This closed-loop approach enables continuous improvement of power optimization by learning from actual device behavior rather than relying on static analysis alone.
2Adaptability or versatility
If battery power is used to run embedded devices, then portability and flexibility are improved, but power consumption limits the operational duration and battery life
Solution Approach 1:
The system performs preliminary analysis by continuously monitoring and storing power consumption data to identify recurring power patterns before they cause battery depletion. By detecting problematic power spikes in advance and providing optimization recommendations, the system enables proactive power management that extends battery life without compromising device portability or flexibility.
3Adaptability or versatility
If embedded devices are used in complex systems, then system functionality is enhanced, but device replacement becomes difficult and power optimization becomes more challenging
Solution Approach 1:
The patent introduces an intermediary power analysis system that sits between the embedded device and the user/developer. This intermediary layer automatically monitors power consumption, identifies problematic patterns, and generates optimization recommendations without requiring direct manipulation or replacement of the embedded device. This approach simplifies the optimization process for complex systems by providing actionable insights that can be implemented through software changes rather than hardware replacement.
4Use of energy by moving object
If power consumption is optimized by identifying peak power patterns, then power usage efficiency is improved, but measurement and detection complexity increases
Solution Approach 1:
The system creates simplified representations (copies) of complex power consumption patterns by identifying and storing characteristic power spike profiles. Instead of analyzing every raw power measurement in detail, the system captures essential pattern features and uses these simplified models to identify problematic code sections. This approach maintains high measurement accuracy while reducing the computational complexity of power pattern detection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for non-intrusive optimization of power consumption by identifying and addressing the most power-intensive functions, resulting in reduced overall power usage and extended battery life for embedded devices without the need for device replacement.
Implementation Method 1
The plurality of power patterns is generated based on a voltage change when an electrical power is supplied to the device
Data Source
AI summary
Disclosed are systems and methods for optimizing power consumption of devices. The system includes monitoring module, generating module, matching module, determining module, and identifying module. The monitoring module monitors a device including program code which further includes power consuming functions. The generating module generates plurality of power patterns corresponding to the power consuming functions. The matching module matches the plurality of power patterns with pre-stored plurality of power patterns to identify one or more power patterns having maximum peak value. The determining module determines occurrence of the one or more power patterns for predefined time interval. The identifying module identifies a power consuming function corresponding to a power pattern based on the occurrence. The generating module generates recommendation for the power consuming function by suggesting changes in a code section of the power consuming function.