Allocation Control Apparatus for Hybrid Cloud Energy Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data analysis techniques in hybrid cloud environments do not efficiently account for electric power consumption, limiting the utilization of renewable energy during data analysis processes.
Innovation Solution
An allocation control apparatus and method that calculates necessary resource and power allocation amounts across multiple sites, using performance and electric power consumption models to determine optimal allocation plans that minimize energy usage, incorporating electric power consumption models to select sites for data and application execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data and applications are allocated without considering electric power consumption, then allocation simplicity is maintained, but renewable energy utilization efficiency deteriorates
Solution Approach 1:
The system performs preliminary calculations of necessary allocation amounts and necessary electric power consumption amounts for each site before making allocation decisions. By pre-computing these values using stored performance models and electric power consumption models, the system prepares optimization data in advance, enabling energy-efficient allocation without increasing real-time decision complexity
Solution Approach 2:
The allocation control apparatus acts as an intermediary between the hybrid cloud environment and the allocation decision-making process. It introduces intermediate calculation steps that determine necessary allocation amounts and power consumption amounts, mediating between raw resource availability and final allocation decisions to optimize renewable energy utilization
2Loss of energy
If allocation decisions are made without electric power consumption models, then processing speed is maintained, but renewable energy utilization deteriorates
Solution Approach 1:
The system stores performance models and electric power consumption models in advance for each site. These models are prepared beforehand to enable rapid calculation of necessary allocation amounts and power consumption amounts when allocation decisions are needed, avoiding time-consuming computations during actual allocation
Solution Approach 2:
The system changes the parameters considered in allocation decisions by incorporating electric power consumption amounts alongside traditional resource allocation parameters. This parameter expansion enables optimization for renewable energy utilization while maintaining efficient processing through structured model-based calculations
3Device complexity
If resource allocation ignores power consumption, then allocation simplicity is maintained, but energy cost increases
Solution Approach 1:
The allocation control apparatus calculates necessary allocation amounts and necessary electric power consumption amounts for each candidate site before making final allocation decisions. This preliminary calculation approach identifies cost-effective allocation options in advance, enabling energy cost optimization without complex real-time control
Solution Approach 2:
The system incorporates electric power consumption amounts as an additional parameter in the allocation decision-making process. By considering this parameter alongside traditional resource allocation metrics, the system optimizes energy cost while maintaining manageable control complexity through structured calculation approaches
Data Source
AI summary
A memory of an application platform stores per site a performance model indicating a relationship between program performance and a resource amount of hardware necessary for realizing program performance, and an electric power consumption model indicating a relationship between a resource allocation amount that is an amount allocated to the program, and an electric power consumption amount consumed when the program is executed. The CPU receives target performance information that indicates target performance for the program, calculates per site a necessary allocation amount and a necessary electric power consumption amount that are a resource allocation amount and an electric power consumption amount necessary for realizing the target performance by using the target performance information, the performance model, and the electric power consumption model, and creates a container/data allocation plan that is an allocation plan of an execution platform of the program and data based on a result of the calculation.