Edge Service Placement Using Combined Network and Cloud Energy Metrics

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Solution Overview

Problem

Existing methods for service placement in edge cloud environments fail to optimize overall energy efficiency, as they do not consider energy consumption in both the edge cloud and cellular network components, leading to suboptimal deployment of edge services.

Innovation Solution

A method and system for energy-efficient service placement that calculates first and second energy efficiency values for edge sites and cellular network components, respectively, and determines a service placement policy based on these values and performance requirements to optimize energy efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by stationary object

If service placement is optimized for edge cloud energy efficiency only, then edge cloud energy consumption is reduced, but cellular network energy consumption is not minimized

Engineering Contradiction:

Improveedge cloud energy efficiencyVSAvoidcellular network energy consumption

Core Design Contradiction:

Use of energy by stationary objectVSLoss of energy

Solution Approach 1:

The patent merges the energy efficiency optimization of edge cloud and cellular network into a unified service placement framework. By calculating combined energy efficiency values that incorporate both edge cloud site energy consumption and cellular network component energy consumption, the system achieves holistic energy optimization rather than isolated optimization of individual components.

Inventive Principle:

Principle #5Merging (Combining)

2Use of energy by stationary object

If service placement is optimized for cellular network energy efficiency only, then cellular network energy consumption is reduced, but edge cloud energy consumption is not minimized

Engineering Contradiction:

Improvecellular network energy efficiencyVSAvoidedge cloud energy consumption

Core Design Contradiction:

Use of energy by stationary objectVSLoss of energy

Solution Approach 1:

Inventive Principle:

Principle #5Merging (Combining)

3Reliability

If edge services are distributed among multiple edge sites to meet performance requirements, then service performance is improved, but energy consumption increases

Engineering Contradiction:

Improveservice performanceVSAvoidoverall energy consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent changes the optimization parameter from isolated energy efficiency metrics to a combined energy efficiency metric that considers both edge cloud and cellular network components. This parameter transformation enables the system to identify service placement configurations that achieve performance requirements while minimizing total energy consumption across the entire system.

Inventive Principle:

Principle #35Parameter changes

4Reliability

If all edge services are deployed in all edge sites, then service availability is maximized, but energy consumption and cost increase significantly

Engineering Contradiction:

Improveservice availabilityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent applies local quality by determining service placement on a per-edge-site basis, evaluating the specific energy efficiency characteristics of each site and its associated cellular network components. This localized evaluation enables differentiated service placement decisions that optimize energy efficiency for each location while maintaining overall service availability.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS20260067161A1Method and system for energy efficient service placement in an edge cloud

Publication Date: 2026.03.05 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

AI summary

A method for an energy-efficient service placement in a mobile edge cloud comprising at least one edge site is disclosed. The method comprises receiving a service placement request from a service provider. The method comprises identifying a set of candidate edge site groups and calculating a first energy efficiency value for each identified candidate edge site group. Further, the method comprises calculating a second energy efficiency value for components of the cellular network that are involved in the communication between the user device and the edge site. The method comprises determining for each candidate edge site group, an energy efficiency metric for deploying said service placement request in a traffic path of the cellular network based on the first and second energy efficiency values. The method further comprises determining a service placement policy for the service placement based on the calculated energy efficiency metric and the obtained performance parameters.