Edge Deployment Manager Energy Optimization
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Solution Overview
Problem
In edge computing environments, power consumption is a critical challenge due to limited power storage in edge devices, which hinders successful workload deployments, and existing solutions focus on specific workloads rather than a holistic end-to-end perspective across multiple nodes.
Innovation Solution
A computer-implemented method and system that employs an Edge Deployment Manager (EDM), Localized Deployment Manager (LDM), and Energy Management Modules (EMM) to monitor and manage energy consumption across edge nodes, creating and updating energy plans to optimize power usage, prioritize workloads, and dynamically adjust resource allocation based on energy characteristics and policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If edge computing moves computational power closer to end users by increasing the number of endpoints, then service delivery and responsiveness are improved, but power consumption increases and becomes critical due to limited power store in edge devices
Solution Approach 1:
The system segments the edge computing environment into multiple edge nodes, each monitored by individual Energy Management Modules (EMMs). This segmentation allows for granular power management at each node level, enabling independent optimization of power consumption for each segment while maintaining overall system productivity.
Solution Approach 2:
The patent implements dynamic power management through continuous monitoring of energy characteristics by EMMs and adaptive adjustment of workload deployment based on real-time power conditions. The system dynamically reallocates workloads between edge nodes according to their current power availability, transforming the static power consumption problem into a dynamically optimized system.
2Manufacturing precision
If existing solutions focus on specific workloads rather than a holistic end-to-end perspective, then workload-specific optimization is achieved, but overall power optimization across multiple nodes is insufficient
Solution Approach 1:
The Energy Management Modules (EMMs) are designed as universal components that can manage power for any type of workload across different edge nodes. The centralized power optimization system provides multi-functional capability by simultaneously managing power for multiple workloads, multiple nodes, and various power sources, achieving holistic power optimization rather than workload-specific optimization.
Solution Approach 2:
The system implements continuous feedback loops where EMMs monitor energy characteristics and power consumption in real-time, report to the centralized optimization system, which then adjusts workload deployment accordingly. This feedback mechanism enables the system to adapt to changing power conditions across the entire edge computing environment, providing holistic power management.
3Power
If more edge nodes are deployed to extend cloud computing to the edge, then computational power availability is improved, but power management complexity increases
Solution Approach 1:
The patent introduces Energy Management Modules (EMMs) as intermediary components between the diverse edge nodes and the centralized optimization system. These EMMs standardize power monitoring and control interfaces, acting as mediators that simplify the management complexity by providing a uniform interface for managing power across heterogeneous edge nodes with different power characteristics.
Solution Approach 2:
Each edge node is equipped with an EMM that autonomously monitors its own energy characteristics and power consumption without requiring manual intervention. The nodes self-report their power status to the centralized system, which automatically makes deployment decisions, reducing the operational complexity of managing multiple edge nodes.
Data Source
AI summary
An approach for managing workload deployment in a distributed network, including edge computing is provided. The approach includes deploying several modules, such as, EMM (energy management module), LDM (localized deployment manager) and EDM (edge deployment manager). These modules will be constantly monitoring and managing the energy consumption at the edge nodes under their purview and communicate with other modules to develop a holistic energy management system (e.g., energy policies, energy algorithms, energy plans, etc.) to ensure the most effective energy management of workload is implemented.