Capability Based Placement for Virtual Machine Resource Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In computing environments with multiple devices, such as virtual servers or cloud computing, determining the appropriate computing resources to assign for customer requests is challenging due to limited pre-defined categories that may not match the specific resource needs.
Innovation Solution
The implementation of capability-based placement of virtual machine instances, where detailed characteristics of server computers and slots are used to determine higher-level capability tags, allowing for the efficient selection of resources that match the requirements of customer requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed hardware and software characteristics are maintained for all computing resources, then resource matching precision is improved, but system complexity and difficulty of management increase
Solution Approach 1:
The patent segments the detailed hardware and software characteristics into discrete capability tags. Each computing resource is described by a set of tagged capabilities (e.g., CPU type, memory amount, storage capacity) rather than maintaining complete detailed specifications. This segmentation allows precise matching by tagging relevant capabilities while ignoring irrelevant details, thereby reducing system complexity while preserving matching precision.
Solution Approach 2:
The patent extracts only the essential capability characteristics needed for matching from the complete detailed specifications of computing resources. By taking out and retaining only the relevant capability tags (such as processor type, memory size, storage capacity) and discarding unnecessary detailed information, the system achieves precise resource matching with reduced complexity and easier management.
2Ease of operation
If pre-defined categories of computing resources are used, then ease of selection is improved, but adaptability to specific resource needs deteriorates
Solution Approach 1:
The patent applies local quality by allowing different capability tags to be assigned to different computing resources based on their specific characteristics. Instead of forcing all resources into uniform pre-defined categories, each resource can have customized capability tags that reflect its local qualities and specific strengths (e.g., high CPU capability, large storage capacity, specialized GPU acceleration), enabling both ease of selection through tagging and adaptability to specific needs.
Solution Approach 2:
The patent changes the parameter representation from fixed pre-defined categories to flexible capability tags with varying parameters. Each computing resource can have capability tags with different parameter values (e.g., memory amount ranging from 8GB to 128GB, storage capacity varying by tier), allowing the system to adapt to specific resource needs while maintaining ease of selection through standardized tag structures.
3Manufacturing precision
If complete lists of hardware and software details are maintained, then resource selection accuracy is improved, but resource utilization efficiency deteriorates due to difficulty in creation, storage, update, and search
Solution Approach 1:
The patent creates a simplified copy or abstraction of the complete hardware and software details by using capability tags. Instead of maintaining and managing complete detailed specifications, the system uses tagged capability representations that capture the essential information needed for accurate resource selection. This copying approach maintains resource selection accuracy while dramatically improving efficiency in creation, storage, update, and search operations.
Solution Approach 2:
The patent makes the capability tag system universal and multi-functional. The same tagged capability structure serves multiple purposes: it enables accurate resource selection, facilitates efficient storage and retrieval, supports rapid updates, and allows flexible searching across multiple dimensions. This universal tagging approach replaces multiple separate detailed lists with a single versatile system that improves both accuracy and efficiency.
Data Source
AI summary
Capability based placement can be used for placing virtual machine instances on server computers (which can be configured to support one or more virtual machine slots) that are capable of running the instances in an efficient manner. For example, capability tags can be determined from the detailed characteristics (e.g., detailed hardware, software, and/or other characteristics) of the server computer and/or slots. For example, capability tags can indicate capabilities such as disk throughput, network bandwidth, database support, encryption support, video editing support, etc. Requests to launch virtual machine instances can be received and capability tags can be determined from the requests. Servers and/or slots that match the determined capability tags can be identified and used for launching the instances.