Dynamic Power Allocation for Host Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Host device performance is often hampered due to the lack of reserve power resources, which existing power management systems fail to address effectively by dynamically allocating electrical power based on workload criticality and resource utilization.
Innovation Solution
A method and system for intelligent power distribution management that identifies power-hungry devices, generates a host priority list based on workload criticality, and allocates reserve electrical power to top-ranked devices using machine learning and artificial intelligence-driven analytics, dynamically managing power allocation between primary and reserve power pools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reserve electrical power is allocated to power-hungry devices, then host device performance is improved, but power resource efficiency deteriorates
Solution Approach 1:
The power allocation system dynamically adjusts power distribution based on real-time workload criticality and resource utilization. The system transitions from static power allocation to dynamic allocation, where the power management service continuously monitors telemetry data and reallocates reserve power to power-hungry devices only when workload criticality thresholds are met, thereby improving performance while maintaining power efficiency.
Solution Approach 2:
The system changes the parameter of power allocation from fixed to variable based on workload characteristics. By introducing parameters such as workload criticality level, resource utilization metrics, and power hunger indicators, the system optimizes power distribution to match actual computational needs, resolving the contradiction between performance and efficiency.
2Productivity
If reserve electrical power is allocated based on workload criticality, then computing resource efficiency is improved, but system complexity increases
Solution Approach 1:
The power management system is segmented into distinct functional components: a power management service for decision-making, telemetry collection modules for data gathering, and power allocation execution modules for implementing decisions. This segmentation allows the complex task of intelligent power distribution to be divided into manageable, modular components that can be independently developed and maintained.
Solution Approach 2:
The power management service acts as an intermediary between the power source and computing devices. It collects telemetry data from devices, analyzes workload criticality, and makes informed decisions about power allocation. This intermediary layer simplifies the overall system architecture by centralizing the complex decision-making logic in a dedicated service rather than distributing complexity across all components.
Data Source
AI summary
A method and system for intelligent power distribution management. Specifically, the disclosed method and system propose allocating (and deallocating) reserve or supplemental electrical power to host devices dynamically based on intelligent analyses of host device telemetry including, but not limited to, workload criticality, workload computing resource utilization, hardware configuration metadata, various operational parameters describing host device state, and measurements (as well as other information) pertinent to electrical power usage.