Cloud Resource Energy Tracking via Segmented Power State Counters
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Solution Overview
Problem
Existing cloud computing systems face challenges in accurately measuring and managing energy consumption across shared, single-tenant, and multi-tenant resources, making it difficult for users to control and optimize energy usage, especially in environments with multiple users and varying resource allocations.
Innovation Solution
Implementing a system with a control plane that monitors and manages energy consumption by attributing usage to specific customers, allowing them to adjust power states and operational modes of resources, and providing tools for customers to view and manage their energy consumption, including options for energy profiles and environmental credits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud computing resources are shared among multiple users, then resource utilization efficiency is improved, but accurate measurement and apportionment of energy consumption among users becomes difficult
Solution Approach 1:
The patent segments energy consumption measurement by implementing separate counters for different power states (active, idle, sleep) and different resource types (CPU, memory, storage, network). This segmentation allows accurate attribution of energy consumption to specific users and resources while maintaining shared infrastructure, resolving the contradiction between resource sharing and measurement accuracy.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring power state transitions and energy consumption, then providing this information back to users through billing systems and energy consumption reports. This feedback enables users to understand their actual energy usage and make informed decisions, while the system maintains accurate measurement through automated tracking of power state changes.
2Loss of energy
If users are given control over power states of cloud resources, then energy consumption optimization is improved, but system complexity and management overhead increase
Solution Approach 1:
The patent implements self-service by allowing users to autonomously control the power states of their allocated resources through user-friendly interfaces. Users can independently transition resources between active, idle, and sleep states based on their energy optimization needs, eliminating the need for complex manual management while maintaining energy efficiency. The system automatically tracks these user-initiated state changes for accurate billing.
3Loss of energy
If detailed energy consumption tracking is implemented, then energy optimization and cost reduction are improved, but data processing and storage requirements increase
Solution Approach 1:
The patent extracts only the essential energy consumption data needed for optimization and billing purposes, rather than tracking all possible system parameters. By focusing specifically on power state transitions and their associated energy costs, the system achieves effective energy optimization while minimizing data processing and storage requirements. Irrelevant detailed system data is excluded from the tracking mechanism.
Data Source
AI summary
Customers in a multi-tenant environment can obtain energy consumption information for a set of resources or other computing components used by those customers, including time-accurate accounting for various components of those resources utilized on behalf of the customer. A customer can also have the ability to specify how the resources are to be operated when used for the customer, in order to manage the amount of energy consumption. The accounting can be performed even when the resources are shared among multiple users or entities. Various hardware components or agents can be used to provide detailed energy consumption information for those components that is associated with a particular customer. The information can be used not only for accounting and monitoring purposes, but also to make dynamic adjustments based on various changes in usage, energy consumption, or other such factors.