18135619. MODELING POWER USED IN A MULTI-TENANT PRIVATE CLOUD ENVIRONMENT simplified abstract (International Business Machines Corporation)

MODELING POWER USED IN A MULTI-TENANT PRIVATE CLOUD ENVIRONMENT

Organization Name

International Business Machines Corporation

Inventor(s)

Sunyanan Choochotkaew of Koto (JP)

Tatsuhiro Chiba of Bunkyo-ku (JP)

Marcelo Carneiro Do Amaral of Tokyo (JP)

Eun Kyung Lee of Bedford Corners NY (US)

MODELING POWER USED IN A MULTI-TENANT PRIVATE CLOUD ENVIRONMENT - A simplified explanation of the abstract

This abstract first appeared for US patent application 18135619 titled 'MODELING POWER USED IN A MULTI-TENANT PRIVATE CLOUD ENVIRONMENT

• • Simplified Explanation:**

The patent application describes techniques for modeling power in a multi-tenant private cloud environment. An absolute power model and a dynamic power model are trained to estimate power usage in the cloud environment.

• • Key Features and Innovation:**

- Absolute power model estimates absolute power in multi-tenant private cloud environment - Dynamic power model estimates dynamic power based on deconstructed inferences - Combined model integrates absolute and dynamic power models for accurate power estimation

• • Potential Applications:**

- Cloud computing infrastructure management - Energy efficiency optimization in data centers - Resource allocation in multi-tenant environments

• • Problems Solved:**

- Inaccurate power estimation in multi-tenant private cloud environments - Lack of dynamic power modeling techniques - Difficulty in optimizing power usage in cloud environments

• • Benefits:**

- Improved accuracy in power estimation - Enhanced energy efficiency in data centers - Better resource allocation in multi-tenant environments

• • Commercial Applications:**

Potential commercial applications include cloud service providers, data center operators, and companies looking to optimize power usage in their IT infrastructure.

• • Prior Art:**

Prior research may include studies on power modeling in cloud environments, dynamic power estimation techniques, and resource allocation algorithms in multi-tenant systems.

• • Frequently Updated Research:**

Stay updated on the latest advancements in power modeling for multi-tenant private cloud environments to ensure optimal resource utilization and energy efficiency.

• • Questions about Power Modeling in Multi-Tenant Private Cloud Environments:**

1. How does the combined model improve power estimation accuracy compared to individual models? 2. What are the key challenges in implementing dynamic power modeling in multi-tenant private cloud environments?

Original Abstract Submitted

Described are techniques for modeling power in the multi-tenant private cloud environment. An absolute power model is trained to estimate the absolute power in the multi-tenant private cloud environment. The absolute power model is composed of both independent and dependent inferences. Furthermore, a dynamic power model is trained to estimate the dynamic power in the multi-tenant private cloud environment based on the deconstructed independent inferences. The dynamic power model is composed of only the deconstructed independent inferences. The absolute power model and the dynamic power model are then combined into a combined model to model the power in the multi-tenant private cloud environment after validating the dynamic power model. The combined model may then be utilized to estimate the power used in the multi-tenant private cloud environment if the error metrics of the combined model indicate that a measured error of the combined model is less than a threshold value.