Virtual Network Function Deployment Planning
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Solution Overview
Problem
Existing solutions for virtualizing network functions are inflexible, often leading to resource wastage or inability to deploy on hardware with less than specified resources, as they follow a 'hardware follows software' paradigm, where static hardware requirements are not adaptable to available hardware capabilities.
Innovation Solution
A method and apparatus that dynamically determine deployment plans for virtual network functions (VNFs) by matching key performance indicators (KPIs) with available execution unit performance characteristics, allowing for flexible implementation and resource optimization, including scaling VNF modules based on hardware availability and topology, using a VNF description template and utility function to select the most effective deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static hardware requirements are specified for VNF modules, then deployment simplicity is improved, but hardware adaptability deteriorates
Solution Approach 1:
The patent implements dynamic hardware requirement specification where VNF module requirements are not fixed but can be adjusted based on available hardware capabilities. The system determines deployment plans by matching VNF performance requirements against actual hardware performance characteristics, allowing the same VNF to be deployed on different hardware configurations (e.g., single server vs. multiple servers) based on what is available in the cloud environment.
2Reliability
If hardware resources are over-provisioned to meet performance requirements, then performance reliability is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent changes the parameters of hardware resource allocation by determining deployment plans that precisely match VNF performance requirements with available hardware capabilities. Instead of over-provisioning, the system evaluates multiple deployment plans and selects those that achieve required performance (e.g., processing capacity, throughput) while minimizing resource consumption. This allows flexible adjustment of resource allocation parameters based on actual needs rather than fixed over-provisioning rules.
3Power
If powerful hardware is required to guarantee performance, then performance capability is improved, but deployment flexibility deteriorates
Solution Approach 1:
The patent segments the VNF deployment into multiple possible configurations that can be adapted to different hardware power levels. Instead of requiring a single powerful hardware configuration, the system divides the deployment into alternative plans (e.g., single server deployment vs. multi-server deployment) where less powerful hardware can be combined to achieve the same performance capability. This segmentation allows deployment on heterogeneous hardware with varying power levels.
4Extent of automation
If static deployment templates are used, then deployment automation is improved, but resource optimization deteriorates
Solution Approach 1:
The patent implements dynamic deployment template generation where the system automatically determines deployment plans by evaluating VNF performance requirements against available hardware characteristics. Rather than using fixed static templates, the automation dynamically adapts the deployment configuration based on real-time hardware availability and performance capabilities, selecting from multiple possible deployment plans to optimize resource utilization while maintaining full automation.
Data Source
AI summary
A method for implementing an entity of a network by virtualizing said network entity and implementing it on one or more servers each acting as an execution unit for executing thereon one or more applications running and/or one or more virtual machines running on said execution unit, each of said application programs or virtual machines running on a server and implementing at least a part of the functionality of said network entity being called a virtual network function VNF module, wherein a plurality of said VNF modules together implement said network entity to thereby form a virtual network function VNF, said method comprising the steps of: obtaining m key performance indicators (KPI) specifying the required overall performance of the VNF, obtaining n performance characteristics for available types of execution units, determining one or more possible deployment plans based on the obtained m KPI and n performance characteristics, each deployment plan specifying the number and types of execution units, such that the joint performance of VNF modules running on these execution units achieves the required overall performance of the VNF.