Virtual Machine Reconfiguration via Negotiated Resource Offers

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Solution Overview

Problem

Current techniques for managing virtual machines in cloud computing environments are inadequate in handling dynamically changing workloads, as they rely on past resource usage data for future resource allocation decisions, which can lead to inefficiencies in resource utilization.

Innovation Solution

A method that allows a virtual machine to request and negotiate reconfiguration of its resource allocation based on anticipated needs, involving a resource controller that assesses available resources and proposes reconfiguration schemes such as runtime, live migration, or offline migration to optimize performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If workload management relies on past resource usage data for future allocation decisions, then resource allocation can be automated, but the system cannot adequately respond to dynamically changing workloads

Engineering Contradiction:

Improveautomated resource allocationVSAvoidresponse to dynamic workloads

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The system performs preliminary actions by monitoring current workload characteristics and anticipating future resource needs before actual resource allocation decisions are required. The workload management entity proactively determines anticipated future resource usage based on current workload analysis, enabling the system to prepare and respond more effectively to dynamic changes rather than merely reacting to past data.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If resource allocation is adjusted based on monitored performance metrics, then system optimization can be achieved, but the response time is delayed due to reliance on historical data

Engineering Contradiction:

Improvesystem optimizationVSAvoidresponse delay

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of current workload characteristics to anticipate future resource requirements before performance degradation occurs. By proactively determining anticipated future resource usage based on current monitoring data rather than historical patterns alone, the system can pre-adjust resource allocation, reducing the time lag between workload changes and optimization responses.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops where current workload performance is monitored in real-time, fed back to the workload management entity, which then adjusts resource allocation dynamically. This closed-loop feedback mechanism enables the system to respond to actual current conditions rather than relying solely on historical data, reducing response delays while maintaining system optimization.

Inventive Principle:

Principle #23Feedback

3Productivity

If virtual machines share physical computing resources, then resource utilization efficiency improves, but resource contention and performance variability increase

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidperformance consistency

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system dynamically adjusts resource allocation to virtual machines based on real-time workload characteristics and anticipated future resource usage. Rather than static resource allocation, the workload management entity continuously monitors current workload and modifies resource distribution dynamically, enabling the system to maintain performance consistency even under resource sharing conditions by adapting to changing demands.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes allocation parameters of virtual machine resources based on monitored workload characteristics and anticipated future needs. By adjusting resource allocation parameters dynamically rather than maintaining fixed allocations, the system can optimize resource utilization efficiency while maintaining performance consistency, as resource distribution adapts to actual workload requirements rather than remaining static.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10754702B2Technique for reconfiguring a virtual machine

Publication Date: 2020.08.25 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

AI summary

A technique for reconfiguring a virtual machine in a cloud computing environment is disclosed. A method implementation of the technique comprises receiving (S310) a reconfiguration request from an application (110) being executed on the virtual machine in the cloud computing environment, the reconfiguration request indicating a desired resource allocation for the virtual machine, sending (S312) a reconfiguration response to the application (110), the reconfiguration response including a reconfiguration offer indicating a possible resource allocation for the virtual machine, receiving (S316) a reconfiguration acknowledgement from the application (110) indicating acceptance of the reconfiguration offer, and triggering (S318) reconfiguration of the virtual machine so as to allocate resources to the virtual machine according to the accepted reconfiguration offer.