Automated Virtual Machine Assignment in Data Center Clusters

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Solution Overview

Problem

In data centers, operators face challenges in efficiently assigning virtual machines to physical devices within a cluster, leading to potential overloading and resource imbalance, which affects the performance and value of the cluster.

Innovation Solution

An operator console is introduced that provides a graphical interface to monitor resource usage, allowing automated selection and assignment of virtual machines to physical devices, enabling operators to manage virtual machines and physical devices without extensive decision-making, by presenting resource information and allowing manipulation of virtual machines and physical devices.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If operators manually assign virtual machines to physical devices, then they can make informed decisions about resource allocation, but the process becomes complex and time-consuming

Engineering Contradiction:

Improveease of virtual machine assignmentVSAvoidtime for decision-making

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system automatically assigns virtual machines to physical devices by evaluating resource availability and cluster state without requiring operator intervention. The assignment logic self-manages the allocation process, selecting appropriate physical devices based on current cluster conditions and virtual machine requirements.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of operator decision-making with an automated computational system. The system uses algorithms to evaluate cluster state, resource availability, and assignment criteria, substituting human cognitive processes with automated computational logic that rapidly determines optimal virtual machine placements.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If virtual machines are assigned without automated selection, then operators maintain control over resource allocation, but load balancing and resource efficiency deteriorate

Engineering Contradiction:

Improvecluster efficiencyVSAvoidcomplexity of assignment process

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system continuously monitors cluster state including resource availability, load balancing metrics, and physical device status. This feedback loop enables the automated assignment process to make informed decisions by evaluating current cluster conditions, ensuring that virtual machines are placed on appropriate physical devices to maintain efficiency and balance resources effectively.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent dynamically evaluates multiple parameters including resource availability, cluster state, and assignment criteria to determine optimal virtual machine placement. By changing and adjusting these parameters based on real-time cluster conditions, the system achieves efficient resource allocation without requiring complex manual intervention.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If physical devices are allowed to operate independently in a cluster, then each device maintains autonomy, but resource imbalance and performance degradation occur

Engineering Contradiction:

Improvecluster stabilityVSAvoidresource utilization

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent merges the independent operation of physical devices into a coordinated cluster-wide assignment process. By combining resource information from all physical devices and evaluating them as a unified system, the automated assignment process ensures balanced resource utilization across the cluster while maintaining the operational independence of individual devices.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system works to create equipotential conditions across the cluster by balancing resource distribution and load across physical devices. Through automated assignment that considers overall cluster state, the system ensures that no single device becomes significantly overloaded or underutilized, maintaining stable and efficient operation throughout the cluster.

Inventive Principle:

Principle #12Equipotentiality

Data Source

PatentUS10430216B1Virtual machine automated selection

Publication Date: 2019.10.01 SCALE COMPUTING INC

AI summary

Assigning virtual machines to physical devices in a cluster, without need for substantial operator decision-making or intervention. An operator console, coupled to the cluster, receives information from those physical devices about resource use by virtual machines. Each physical device reports virtual machines assigned thereto, and their resource usage. The console presents information regarding resource use by virtual machines, and presents a control panel to the operator, allowing manipulation of virtual machines and physical devices: starting or stopping virtual machines, moving virtual machines, adding or removing physical devices. The operator can create a new virtual machine, or can restart a paused or stopped virtual machine. The console determines a best physical device to host the new virtual machine, assigns the new virtual machine to that selected physical device, and starts or restarts the new virtual machine on the selected physical device, without substantial operator decision-making or intervention.