Network Resource Management Server Test Allocation
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Solution Overview
Problem
Existing resource management methods in cloud technology struggle to provide reliable and efficient resource allocation due to parameter differences and unknown environmental conditions, leading to suboptimal performance and increased maintenance costs.
Innovation Solution
A resource management method where a management server forms a test server by combining reserved network resources and applies it if the test server meets predetermined conditions, using a resource information table and job management information to select and evaluate resources based on extraction probability and performance results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resource allocation is improved through calculation methods, then resource utilization efficiency is enhanced, but reliability deteriorates due to parameter differences and unknown environmental conditions
Solution Approach 1:
The system performs preliminary actions by creating test servers with candidate resource allocations before actual deployment. Multiple test servers are generated with different resource distribution schemes, and their performances are evaluated in advance through simulation. The allocation that demonstrates superior performance in testing is then selected for actual deployment, ensuring both efficiency improvement and reliability through pre-validation.
2Productivity
If calculation-based optimization is applied, then resource allocation performance is improved, but time consumption increases due to parameter verification and environmental condition analysis
Solution Approach 1:
The system creates virtual copies of servers (test servers) that replicate the characteristics of actual servers without requiring physical hardware. These test servers are instantiated as virtual environments where resource allocation schemes can be tested rapidly. By copying server configurations and testing them in virtualized environments, the system achieves fast optimization iteration without the time penalty of physical hardware provisioning and testing.
3Measurement precision
If comprehensive parameter verification is performed, then allocation accuracy is improved, but device complexity increases due to multiple checking requirements
Solution Approach 1:
The test server evaluation process is designed to be self-service, where test servers automatically execute predefined workloads and collect their own performance metrics. Each test server independently measures its resource utilization efficiency, throughput, and other key indicators without requiring external intervention. This self-evaluation mechanism simplifies the management system architecture while maintaining comprehensive verification accuracy, as the system leverages the inherent capabilities of the test servers themselves to generate evaluation data.
Data Source
AI summary
In order to effectively use the resources on a network, there is provided a management server (200) for selecting each resource of a resource information table (211) as a test resource, if the extraction probability for each resource is equal to or greater than the random numbers probability generated by a random number generation part (221), forming a test server by combining the selected resources, performing the job by using the formed test server, and applying the test server as the server of the particular network if the execution result of the job meets the job determination method.