Energy Consumption Report Analysis for Software Applications
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Solution Overview
Problem
Current software testing methods struggle to effectively monitor and analyze energy consumption of remote devices, especially those with limited resources, as they cannot capture comprehensive data on all possible environmental conditions and code paths, leading to inefficiencies and potential resource overconsumption.
Innovation Solution
Implement a system where remote devices generate energy consumption reports by capturing snapshots of call stacks during high energy usage, which are then processed on a server to identify representative call stacks and energy signatures, allowing for categorization and analysis to optimize application performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software applications are tested in controlled clean room environments before distribution, then testing can be performed under known conditions, but it is impossible to test every possible variation of environments and conditions that users may experience
Solution Approach 1:
The system enables remote devices to autonomously collect and report their own energy consumption data and call stack information without requiring physical connection to diagnostic equipment. This self-service approach allows the software to be tested in the actual environmental conditions where users operate it, rather than in controlled clean room environments, thereby achieving both reliability and environmental versatility.
Solution Approach 2:
A server acts as an intermediary between remote devices and developers. The server collects energy consumption reports from multiple remote devices operating in various environments, processes the data, and provides insights to developers. This intermediary system enables comprehensive environmental coverage by aggregating data from diverse real-world conditions while maintaining reliable testing through centralized analysis.
2Reliability
If comprehensive testing of every code path is performed before release, then software correctness can be ensured, but it becomes very difficult and cost prohibitive as applications grow in complexity and size
Solution Approach 1:
The system implements continuous feedback by collecting energy consumption data and call stack information from remote devices after deployment. This feedback loop allows developers to identify frequently executed code paths and potential issues in production environments, enabling targeted testing and optimization without requiring exhaustive pre-release testing of all code paths regardless of application complexity.
Solution Approach 2:
Instead of attempting to test every single code path before release (excessive action), the system focuses on collecting and analyzing energy consumption data from actual usage to identify the most critical code paths that require attention. This partial action approach prioritizes testing efforts on the most impactful areas while reducing overall testing costs and complexity.
3Adaptability or versatility
If energy consumption monitoring is performed on remote devices without physical connection, then data can be collected from all devices in real environments, but gathering testing and diagnostic data from remote devices is generally not possible
Solution Approach 1:
The system replaces the mechanical connection requirement (physical USB or wired connection to diagnostic equipment) with a software-based monitoring approach. Energy consumption sensors and debugging tools integrated into the remote device itself collect and transmit data wirelessly to the server, eliminating the need for physical connections while maintaining full data availability for testing and analysis.
Data Source
AI summary
Embodiments of the present disclosure include methods and systems for generating and processing energy consumption reports received from a plurality of devices. The reports may include a plurality of call stacks captured and stored by remote device as a result of an energy consumption of the corresponding device. For each energy consumption report, the plurality of call stacks may be analyzed to determine a representative call stack of the energy consumption report. The energy consumption reports may be assigned to one or more of a plurality of energy consumption categories based on distances between the representative call stacks of the energy consumption reports and corresponding representative call stacks of the energy consumption categories. A request may be received for energy consumption reports for a particular energy consumption category. Upon receiving the request, providing a representative set of energy consumption reports assigned to the particular energy consumption category.