Network Slice Scaling via Cost Effectiveness Metrics
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Solution Overview
Problem
Current network slice scaling methods in 5G communications networks do not prioritize slices based on cost effectiveness, leading to inefficient resource allocation and potential service disruptions due to static resource management, where slices with higher revenue potential may be denied resources while those with lower cost effectiveness are prioritized.
Innovation Solution
Implement a method where nodes in the communications network assess the cost effectiveness of network slices by collecting revenue, resource availability, and cost data to prioritize scaling requests, ensuring that slices with higher revenue potential are prioritized for resource allocation, even during resource scarcity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If network slice scaling is performed using static resource management, then resource allocation is simplified, but resource allocation efficiency deteriorates as high-revenue slices may be denied resources while low cost-effectiveness slices are prioritized
Solution Approach 1:
The patent implements dynamic resource allocation by introducing cost effectiveness metrics that allow the system to adapt resource distribution based on real-time slice performance and revenue data, transitioning from static to dynamic management to improve allocation efficiency
Solution Approach 2:
The patent changes the allocation parameter from uniform static allocation to cost-effectiveness-based dynamic allocation by introducing new parameters including revenue metrics, cost metrics, and cost effectiveness calculations that determine resource distribution priorities
2Productivity
If cost effectiveness assessment is implemented for network slice scaling, then resource allocation efficiency improves, but system complexity increases due to additional data collection and analysis requirements
Solution Approach 1:
The patent applies multi-functionality by designing the cost effectiveness assessment mechanism to simultaneously perform multiple functions: revenue evaluation, cost analysis, slice prioritization, and resource allocation decision-making, thereby managing complexity through consolidated multi-purpose evaluation
Solution Approach 2:
The patent implements feedback loops where resource allocation decisions are continuously refined based on monitored cost effectiveness metrics, creating a self-adjusting system that learns from performance data to optimize future allocation decisions
3Ease of operation
If uniform resource allocation is used across all network slices, then operational simplicity is maintained, but revenue optimization deteriorates as high-revenue slices do not receive prioritized resources
Solution Approach 1:
The patent applies local quality by differentiating resource allocation treatment for different network slices based on their individual cost effectiveness characteristics, allowing high-revenue slices to receive prioritized resources while maintaining simplified operations through automated differentiation rules
Data Source
AI summary
A method, performed by a first node (111). The method is for handling scaling of a network slice in a communications network (100). The first node (111) operates in the communications network (100). The first node (111) obtains (203), from a second node (112) operating in the communications network (100), a request to scale a network slice. The first node (111) then determines (204) whether or not to scale the network slice. The determining (204) is based on a cost effectiveness of the network slice.