Virtual Machine Resource Allocation via Latency Proportionality
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Solution Overview
Problem
The increasing complexity of shared hardware in virtual machine environments makes manual assignment of system resources challenging, particularly as the size and complexity of underlying hardware grow.
Innovation Solution
A method and system that automatically specify the layout of computing system resources by receiving requests for virtual machines, calculating resource groupings' proportionality based on processor and memory requirements, sorting resource groupings, and binding the appropriate resource groups to satisfy processor and memory needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual assignment of system resources is used, then resource allocation can be controlled, but the difficulty of assignment increases greatly as hardware size and complexity increase
Solution Approach 1:
The system performs self-service by automatically gathering resource grouping information, calculating proportionality metrics, sorting resource groupings, and binding resources to virtual machines without human intervention. The resource allocation system serves itself by implementing the entire assignment process through automated algorithms rather than requiring manual administrator input for each allocation decision.
Solution Approach 2:
The patent replaces the mechanical manual assignment process with an automated computational system. Instead of administrators manually analyzing hardware complexity and making assignment decisions, the system uses processors to gather data, calculate proportionality metrics, sort resource groupings algorithmically, and bind resources automatically, substituting human mechanical operations with automated computational mechanisms.
2Ease of operation
If automated resource allocation is implemented, then assignment difficulty is reduced, but complexity of resource grouping calculation increases
Solution Approach 1:
The automated allocation process is segmented into distinct operational stages: gathering resource grouping information with latency penalties, calculating proportionality metrics for each grouping, sorting the resource groupings based on proportionality, and binding resources to virtual machines. This segmentation breaks down the complex allocation task into manageable, sequential steps that can be automated independently.
Solution Approach 2:
The system performs preliminary actions by gathering resource grouping information and calculating proportionality metrics before the actual resource binding occurs. By pre-calculating the proportionality of each resource grouping and sorting them in advance, the system prepares the allocation data structure beforehand, making the final binding operation simpler and more efficient.
3Productivity
If resource groupings are sorted by proportionality, then resource utilization is optimized, but calculation time increases
Solution Approach 1:
The system calculates proportionality for resource groupings based on the minimum of processor requirement satisfaction and memory requirement satisfaction, rather than evaluating all possible resource combinations. This partial action approach computes only the necessary proportionality metric needed for sorting and binding, avoiding excessive calculation while still achieving optimized resource utilization through proportionality-based allocation.
Data Source
AI summary
A method for specifying the layout of computing system resources includes receiving a request for a virtual machine, the request comprising a processor requirement and a memory requirement, gathering resource groupings, each resource grouping comprising a latency penalty between a processor and at least a memory. The method further includes calculating a proportionality for each resource grouping, wherein the proportionality comprises a minimum of: an amount of the processor requirement the resource grouping can satisfy and an amount of the memory requirement the resource grouping can satisfy, sorting the resource groupings based on at least the proportionality for each resource grouping to create an ordered list and binding, based on the ordered list, at least one resource group to the virtual machine, wherein the at least one resource group satisfies the processor requirement and the memory requirement.