Microserver Load Migration for Power Optimization
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Solution Overview
Problem
Microserver systems face inefficiency due to maintaining microservers in an idle state for extended periods, leading to reduced power efficiency and increased power consumption.
Innovation Solution
A controller-based system that determines application loads across microservers and migrates applications to optimize load distribution, consolidating them on a minimum number of active microservers while powering down inactive ones to a low-power mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If microservers are maintained in an idle state for extended periods, then system availability is improved, but power consumption increases
Solution Approach 1:
The system dynamically transitions microservers between active and low-power states based on real-time load conditions. The controller monitors application loads and adjusts the operational state of each microserver, making the system adaptable rather than static. This resolves the contradiction by allowing microservers to be idle (available) without continuously consuming full power.
Solution Approach 2:
The patent changes the power state parameter of microservers from a fixed state to a variable state. By implementing low-power modes and dynamically adjusting power consumption levels based on workload requirements, the system maintains availability while reducing energy waste during idle periods.
2Use of energy by moving object
If applications are consolidated on fewer microservers, then power efficiency is improved, but load distribution balance deteriorates
Solution Approach 1:
The controller continuously monitors application loads on each microserver and uses this feedback to make informed decisions about migration and consolidation. This closed-loop control ensures that load distribution remains balanced while achieving power efficiency through consolidation, as the system responds to actual load conditions rather than using static rules.
Solution Approach 2:
The system performs preliminary load analysis and capacity assessment before migrating applications. By evaluating whether destination microservers have sufficient capacity and whether consolidation will maintain balance, the system prevents overload conditions and ensures smooth load distribution during and after consolidation.
3Use of energy by moving object
If applications are migrated between microservers, then power consumption is reduced, but system complexity increases
Solution Approach 1:
The controller serves as an intermediary that manages the complexity of application migration. It handles load analysis, migration decision-making, and coordination between microservers, isolating the complexity from the microservers themselves. This allows power consumption reduction through migration while containing system complexity within the control layer.
Data Source
AI summary
Examples of the disclosure include a microserver system comprising a plurality of microservers, a common hardware bus interconnecting the microservers, each microserver of the plurality of microservers being configured to execute one or more applications, and a controller coupled to the plurality of microservers, the controller being configured to determine, based on application-load data associated with the one or more applications, a first application load of a first set of one or more applications executed by a first microserver of the plurality of microservers and a second application load of a second set of one or more applications executed by a second microserver of the plurality of microservers, determine that a combination of the first application load and the second application load is below a maximum-application-load threshold of the second microserver, and migrate the first set of one or more applications from the first microserver to the second microserver.