Sustainability Engine for Function Placement in Heterogeneous Compute Environments

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Solution Overview

Problem

In computing environments, determining the optimal location to run a function to meet sustainability goals is challenging due to uncertainties in energy consumption and varying environmental conditions across different data centers, edge systems, and client environments, making it difficult to provide energy consumption metrics and align with sustainability objectives.

Innovation Solution

A sustainability engine dynamically places functions by analyzing sustainability values, recommending placements across various resources and environments, considering factors like energy efficiency, latency, and regulatory compliance, and tracking performance to optimize function placement and resource utilization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If functions are placed in heterogeneous compute environments (data centers, edge systems, client environments), then sustainability goals such as energy efficiency may be improved, but uncertainty in energy consumption metrics and inability to provide accurate energy consumption data worsen

Engineering Contradiction:

Improveenergy efficiencyVSAvoidenergy consumption metric accuracy

Core Design Contradiction:

Use of energy by moving objectVSMeasurement precision

Solution Approach 1:

The system implements feedback mechanisms by monitoring actual energy consumption of processes in heterogeneous environments and using this data to refine placement recommendations. The sustainability engine continuously gathers performance data from multiple environments and adjusts function placement decisions based on observed energy consumption patterns, transforming uncertain measurements into actionable insights.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system enables self-service by allowing the sustainability engine to automatically characterize energy consumption of processes through inference and modeling. Rather than requiring manual measurement or precise prior knowledge, the system autonomously builds understanding of process energy profiles by observing behavior across different environments and making intelligent placement decisions.

Inventive Principle:

Principle #25Self-service

2Reliability

If process energy consumption is measured in different computational environments, then sustainability alignment may be improved, but variability in process behavior due to region-specific considerations increases uncertainty

Engineering Contradiction:

Improvesustainability goal alignmentVSAvoidprocess behavior variability

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system applies local quality by tailoring function placement decisions to specific environmental characteristics. The sustainability engine analyzes region-specific factors such as local energy sources, environmental conditions, and workload patterns, then makes placement recommendations optimized for each location's unique sustainability profile rather than applying uniform criteria across all environments.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system utilizes parameter changes by dynamically adjusting placement decisions based on varying environmental parameters. The sustainability engine monitors changes in energy consumption patterns, resource availability, and operational conditions across different computational environments, then adapts function placement to optimize sustainability goals under changing conditions.

Inventive Principle:

Principle #35Parameter changes

3Ease of operation

If optimal function placement is determined without sustainability considerations, then deployment simplicity is maintained, but ability to meet sustainability goals deteriorates

Engineering Contradiction:

Improvedeployment simplicityVSAvoidsustainability goal achievement

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system introduces an intermediary sustainability engine that sits between the function deployment process and the heterogeneous compute environments. This intermediary component automatically analyzes sustainability metrics, evaluates placement options, and provides recommendations without requiring complex manual intervention. The intermediary handles the complexity of sustainability optimization while maintaining relative simplicity for users through automated decision support.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20230368107A1System and method of process placement recommendation based on inferred sustainability advantages for sustainable energy efficiency

Publication Date: 2023.11.16 DELL PROD LP

AI summary

Generating function placement recommendations and deploying functions in a manner that accounts for sustainability concerns. Function placements decisions are made that account for sustainability values. When a resource request is received, sustainability values are identified. The resources needed to fulfill the resource request are identified based on the sustainability values and available resources. The identified resources are potential placements for deploying the functions. A specific placement is selected, and the function is deployed to the corresponding resources.