Service Deployment Scoring for Energy-Efficient Edge Distribution
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Solution Overview
Problem
Distributed computing systems, particularly edge devices, face challenges in energy efficiency due to limited processing capabilities and poor network connectivity, leading to increased battery drain and reduced performance without a standardized method for assessing energy efficiency.
Innovation Solution
A system that determines usage and energy metrics, along with node capabilities, to assign scores for deploying services on nodes, prioritizing the most energy-efficient nodes for service instantiation, and dynamically adjusts deployments based on changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If services are deployed on edge devices with limited processing capabilities, then responsiveness and speed are improved by bringing computing power closer to data source, but energy consumption increases and battery drain accelerates
Solution Approach 1:
The system dynamically changes deployment parameters by evaluating multiple factors (energy metrics, usage metrics, node capabilities) and assigning scores to different nodes. This allows the system to adapt service deployment based on current energy conditions, switching between edge devices and other locations to optimize the balance between responsiveness and energy consumption.
2Loss of energy
If conventional energy management solutions optimize service scheduling and migration, then energy consumption is reduced, but lack of standardized energy efficiency assessment limits effectiveness
Solution Approach 1:
The system replaces conventional energy management approaches with a comprehensive scoring mechanism that integrates multiple metrics (energy metrics, usage metrics, node capabilities) and standardized assessment criteria. This substitution enables more precise energy efficiency evaluation by systematically considering diverse factors rather than relying on simplified conventional methods.
Data Source
AI summary
Some examples of the present disclosure relate to data service distribution based on energy efficiency. In one particular example, a system can receive a request to instantiate a service on a node of a plurality of nodes. The system can determine a usage metric associated with the service using a resource of the node, an energy metric associated with energy usage of the service, and a plurality of node capabilities for the plurality of nodes. The system can determine, based on the usage metric, the energy metric, and the plurality of node capabilities, scores associated with deploying the service on each node of the plurality of nodes. The system can deploy the service on a first node of the plurality of nodes based on a first score associated with the first node being higher than a second score associated with a second node of the plurality of nodes.