Virtual Resource Processing for Cloud Disk and VPC Network Bottlenecks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current public cloud vendors use hardware offload cards for cloud disks and VPC networks, leading to limited bandwidth and throughput, resulting in long data processing times for cloud disk and VPC network operations.
Innovation Solution
A virtual resource processing method that acquires data processing requests, determines resource consumption results for virtual storage and network modules, and adjusts virtual resources dynamically based on these results to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hardware offload cards are used for cloud disks and VPC networks, then network bandwidth and storage throughput are limited, but data processing time increases
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring resource consumption results and adjusting virtual resource allocation in real-time. The system transitions from static bandwidth limits to dynamic adjustment based on actual workload, allowing the virtual storage and network modules to adapt their resource consumption patterns to match current data processing demands, thereby reducing data loading and distributing time.
Solution Approach 2:
The system changes the parameters of virtual resource allocation by adjusting the resource consumption results of virtual storage and network modules based on monitored data processing requests. By modifying allocation parameters dynamically rather than using fixed hardware offload card limitations, the system improves data processing speed while managing resource consumption effectively.
2Productivity
If static bandwidth limits are set for VPC and storage networks, then resource allocation is simple, but resource utilization rate decreases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors resource consumption results from data processing requests and uses this information to adjust virtual resource allocation. This closed-loop feedback system automatically optimizes resource utilization rates by allocating more resources to high-demand operations and less to low-demand operations, eliminating the need for manual static configuration while improving overall productivity.
Solution Approach 2:
The system enables self-service resource allocation where the virtual storage and network modules automatically adjust their own resource consumption based on monitored workload patterns. The modules serve themselves by dynamically allocating resources according to actual needs without external intervention, thereby improving resource utilization while managing complexity through automation.
Data Source
AI summary
Embodiments of the present specification provide a virtual resource processing method and apparatus, where the virtual resource processing method includes: acquiring a data processing request received by a network card driver module within a preset time period; determining, according to a data processing type corresponding to the data processing request, a first resource consumption result corresponding to a virtual storage module of a target virtual machine and a second resource consumption result corresponding to a virtual network module of the target virtual machine; and adjusting, according to the first resource consumption result and/or the second resource consumption result, virtual resources of the virtual storage module and the virtual network module.