Cloud Resource Evaluation System for VNF Deployment Accuracy
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Solution Overview
Problem
Current public cloud service providers' performance metrics are simplistic and inadequate for determining the appropriate resource elements for deploying virtual network functions, leading to challenges in dimensioning deployments, adhering to service-level agreements, and managing scalability.
Innovation Solution
A method is introduced that evaluates multiple candidate resource elements by deploying instances of each candidate in a public cloud, collecting performance metrics, and generating reports to select the optimal resource element and determine the necessary number of instances, ensuring compliance with service-level agreements and efficient scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simplistic performance metrics published by CSPs are used, then deployment process is simple, but deployment accuracy and ability to meet performance needs deteriorates
Solution Approach 1:
The patent introduces an intermediary evaluation system that acts as a mediator between CSPs' simplistic published metrics and the actual performance needs of VNFs. This system deploys test instances, collects detailed performance data, and generates comprehensive evaluation reports, thereby bridging the gap between simple published information and accurate performance requirements without requiring complex direct measurements by the user.
Solution Approach 2:
The patent applies preliminary action by conducting performance evaluations and generating detailed reports before actual VNF deployment decisions are made. The system pre-deploys test instances, collects performance metrics, and creates evaluation reports in advance, allowing users to make informed deployment decisions based on pre-analyzed performance data rather than relying on simplistic published metrics.
2Measurement precision
If detailed performance evaluation is conducted by deploying test instances, then deployment accuracy improves, but device complexity and resource consumption increases
Solution Approach 1:
The patent implements universality by creating a multi-functional evaluation system that can assess multiple candidate resource elements across different CSPs using a standardized approach. The system performs various functions including deploying test instances, collecting performance metrics, analyzing data, and generating comprehensive reports, thereby achieving high measurement precision through a unified platform rather than multiple specialized tools.
Solution Approach 2:
The patent applies copying by deploying temporary test instances that replicate the intended VNF deployment configuration. These copy instances are used to collect performance data without affecting production systems, allowing accurate performance evaluation while maintaining system stability and enabling reversible testing.
3Measurement precision
If multiple candidate resource elements are evaluated, then selection accuracy improves, but time and computational resources required increases
Solution Approach 1:
The patent applies partial action by evaluating a selective subset of candidate resource elements based on relevance to the specific VNF deployment requirements. Rather than exhaustively testing all possible resource elements across all CSPs, the system identifies and evaluates only those candidates that are most likely to meet the performance needs, thereby reducing evaluation time while maintaining selection accuracy.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting evaluation criteria, metric thresholds, and candidate selection parameters based on the specific VNF type and performance requirements. The system can modify evaluation parameters such as traffic patterns, load conditions, and performance thresholds to optimize the balance between evaluation thoroughness and time consumption for different deployment scenarios.
Data Source
AI summary
Some embodiments of the invention provide a method of deploying tenant deployable elements on resource elements in public cloud datacenters. The method receives a request to deploy a particular tenant deployable element in one of a first public cloud datacenter (PCD) and a second PCD, the first public cloud datacenter belonging to a first cloud service provider (CSP) and the second public cloud datacenter belonging to a second CSP. For each candidate resource element in the first PCD, the method identifies a first set of performance metrics associated with the candidate resource element. For each candidate resource element in the second PCD, the method identifies a second set of performance metrics associated with the candidate resource element. The method evaluates the identified first and second sets of metrics to select a resource element to implement the particular tenant deployable element in one of the first and second PCDs. The method uses the selected resource element to implement the particular tenant deployable element in one of the first and second PCDs.