Slice Manager Resource Deployment via End-to-End Topology
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Solution Overview
Problem
Current slice resource management technologies fail to optimize resource deployment, leading to suboptimal utilization of resources in network slice deployments, as they do not consider end-to-end resource information and relationships between sub-slices.
Innovation Solution
The proposed solution involves a method and device for slice resource deployment that combines end-to-end resource information to optimize resource allocation across sub-slices, using a slice manager that collects and filters resource information from multiple platforms to determine optimal deployment positions based on SLA requirements, resource capacity, and network connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If only deployment request information is considered for slice resource deployment, then the deployment process is simple, but resource utilization is suboptimal
Solution Approach 1:
The system pre-collects end-to-end resource information from multiple platforms before deployment decisions are made. This preliminary action enables the deployment module to make informed decisions based on comprehensive resource status, achieving optimal resource utilization without complicating the deployment process itself.
Solution Approach 2:
A resource information management module acts as an intermediary between resource platforms and the deployment module. This intermediary collects, filters, and manages end-to-end resource information, allowing the deployment process to remain simple while benefiting from comprehensive resource visibility through the intermediary layer.
2Productivity
If end-to-end resource information is collected and used for deployment, then resource utilization is optimized, but system complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: resource information management module for collecting and filtering data, and deployment module for making deployment decisions. This segmentation allows complex end-to-end resource information processing to be handled by a dedicated module while keeping the overall system architecture clean and manageable.
Solution Approach 2:
The resource information management module serves as an intermediary that handles the complexity of collecting, filtering, and managing end-to-end resource information from multiple platforms. This intermediary absorbs the complexity, allowing the deployment module to operate with simplified inputs while still achieving optimal resource utilization.
3Manufacturing precision
If resource information from multiple platforms is collected and filtered, then optimal deployment positions are determined, but time consumption increases
Solution Approach 1:
Resource information from multiple platforms is collected and filtered in advance before deployment decisions are required. This preliminary processing of resource information enables quick deployment decisions to be made later, as the complex information gathering and filtering work has already been completed.
Solution Approach 2:
The system implements feedback mechanisms where resource information is continuously collected and updated from multiple platforms. This feedback loop enables the system to maintain accurate end-to-end resource visibility, allowing optimal deployment positions to be determined based on current resource status without excessive time consumption during the actual deployment process.
Data Source
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AI summary
Provided is a slice resource deployment method and device, a slice manager and a computer storage medium. The method includes: an overall slice resource deployment request is acquired; a resource deployment position corresponding to each sub-slice is obtained according to the overall slice resource deployment request and pre-acquired end-to-end resource information, the end-to-end resource information including an end-to-end resource network Topology (TOPO) relationship and end-to-end resource running information; and slice resource deployment is performed according to the resource deployment position corresponding to each sub-slice.