Data Center Workload Control Using Spatial And Temporal Migration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data center systems face challenges in optimizing renewable energy utilization ratios due to unstable renewable energy supplies and the inability to freely migrate workloads between data centers, leading to potential downtimes and unadjustable power demand.
Innovation Solution
A data center system and method that controls workload migration between and within data centers, utilizing a processor to manage excess power and migratable time ranges, allowing for both spatial and temporal adjustments to optimize power consumption based on renewable energy availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If workload migration between DC bases is implemented to optimize renewable energy utilization, then renewable energy utilization ratio is improved, but downtime occurs and migration flexibility is reduced
Solution Approach 1:
The system dynamically adjusts workload migration strategies based on real-time renewable energy supply conditions and demand predictions. The control method adapts migration timing and destination based on changing energy availability, allowing the system to optimize renewable energy utilization while minimizing disruption to workload execution.
Solution Approach 2:
The system performs preliminary actions by predicting future renewable energy supply and demand patterns, then planning workload migrations in advance. This allows workloads to be scheduled for migration during periods of high renewable energy availability, reducing the need for disruptive real-time migrations and minimizing downtime.
2Use of energy by moving object
If temporal control of workloads is implemented to match supply and demand, then renewable energy utilization is improved, but workload execution time is delayed
Solution Approach 1:
The system changes temporal parameters of workload execution by adjusting start times, execution durations, and scheduling intervals based on predicted renewable energy supply patterns. This allows workloads to be executed during periods of high renewable energy availability, optimizing energy utilization while managing execution delays through intelligent parameter adjustment.
3Use of energy by moving object
If spatial control of workloads between DC bases is implemented to balance power demand, then renewable energy utilization is improved, but system complexity increases
Solution Approach 1:
The control method implements a universal approach that handles both temporal and spatial workload control through a single integrated framework. The system can migrate workloads between DC bases, delay execution within the same base, or combine both strategies, providing multi-functional control capabilities that simplify the overall system architecture while achieving optimal renewable energy utilization.
Data Source
AI summary
Power demand at each base is adjusted so as to improve a renewable energy utilization ratio at all bases. An inter-base workload control system manages an amount of excess power obtained by subtracting a power supply amount of the renewable energy power supply from a power consumption amount associated with execution of a workload in a future time range at the bases, spatial migratable time range information on a spatial migratable time range where spatial migration of migrating the workload in a future time range at the bases to another base is possible and temporal migratable time range information on temporal migration of delaying execution of the workload in the future time range at the bases within the same base and migrating the workload to another time range and a predicted amount of power consumption through execution of the workload in the future time range at the bases.