Software Power Consumption Monitoring via Resource Status Tracking
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Solution Overview
Problem
Existing data processing systems lack a precise and dynamic method to monitor power consumption, particularly influenced by software applications and their resource usage, which hinders effective energy optimization.
Innovation Solution
A method that monitors software application activities, tracks resource usage, detects resource status, and estimates power consumption using predefined datasheets to provide a detailed and dynamic assessment of power usage across multiple system resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional power monitoring methods are used that only track device-level consumption, then the monitoring system is simple to implement, but the power consumption measurement precision is insufficient because it cannot account for software application influence
Solution Approach 1:
The patent segments the power consumption monitoring into multiple hierarchical levels: software application level, resource level, and device level. Each level has its own monitoring components that work together to provide comprehensive measurement. This segmentation allows precise attribution of power consumption to specific software applications while maintaining a modular system architecture that manages complexity.
Solution Approach 2:
The patent introduces intermediary components including power consumption models, resource usage trackers, and correlation mechanisms that bridge the gap between software application activities and physical power consumption. These intermediaries translate software-level metrics into power consumption estimates, enabling precise measurement without directly instrumenting every hardware component.
2Measurement precision
If detailed software application-level power monitoring is implemented, then the power consumption attribution accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The patent pre-establishes power consumption models for each resource type and configuration before actual monitoring begins. These models contain pre-calculated relationships between resource usage patterns and power consumption. During runtime, the system only needs to query these pre-built models rather than performing complex calculations, significantly reducing real-time data processing complexity while maintaining high attribution accuracy.
Solution Approach 2:
The patent creates simplified copies or representations of the complex power consumption relationships through power models. Instead of directly measuring and processing all raw power data, the system uses modeled representations that capture the essential relationships between software applications, resources, and power consumption. This copying approach reduces data processing complexity while preserving attribution accuracy.
3Productivity
If real-time power consumption monitoring is implemented across all resources, then the energy optimization capability is improved, but the energy consumption of the monitoring system itself increases
Solution Approach 1:
The patent implements selective monitoring that focuses on the most critical software applications and resources rather than uniformly monitoring everything at maximum detail. The system can dynamically adjust the monitoring granularity and frequency based on priority levels, allowing energy optimization for high-priority components while reducing monitoring overhead for less critical components, thus optimizing the trade-off between optimization capability and monitoring overhead.
Solution Approach 2:
The patent dynamically changes monitoring parameters such as sampling frequency, detail level, and activation thresholds based on system conditions. During low-activity periods or for low-priority applications, the monitoring intensity is reduced. During high-activity periods or for critical applications, monitoring intensity increases. This adaptive parameter adjustment allows the system to maintain energy optimization capability while minimizing the energy consumption of the monitoring system itself.
Data Source
AI summary
A method and system for monitoring power consumption of software applications. In a preferred embodiment of the present invention, a new feature is inserted in a system availability monitoring product which estimates the power consumption of the system, starting from the measurement of some parameters collected by a monitoring tool. All systems are impacted by energy consumption, by the usage of its resources (hard-disk, CPU, memory, CDROM, etc.); when the usage of these components increases, the energy consumption increases too. The usage of the resources can be calculated through the monitoring tool according to some specific parameters. The calculated metrics of the usage are based on the measurement of the time during which a resource is in a predetermined status. Each resource has an associated table for determining the expected power consumption according to the status.