Access Point Tagging for Legacy Network Slice Allocation
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Solution Overview
Problem
Legacy devices not programmed with network slices in mind cannot benefit from network slicing, leading to inefficient communication in 5G networks.
Innovation Solution
Implement a system where access point devices use machine learning models to determine appropriate network slices for untagged network traffic by analyzing similarity with tagged traffic, leveraging core management devices for aggregated information and configuration data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network slicing is implemented in 5G networks, then network traffic allocation efficiency is improved, but legacy devices cannot benefit from network slicing
Solution Approach 1:
The patent introduces an access point device as an intermediary between legacy devices and the network slice selection function. The access point captures network traffic from legacy devices, determines appropriate network slices based on traffic characteristics, and forwards traffic through selected network slices. This intermediary enables legacy devices to benefit from network slicing without requiring modifications to the devices themselves.
Solution Approach 2:
The patent creates a virtual representation of network slice capabilities at the access point level, allowing legacy devices to be routed through appropriate network slices without the devices needing to understand or support network slicing natively. The access point copies or replicates the network slice selection functionality that would normally reside in the core network, enabling legacy device compatibility.
2Productivity
If network slicing is implemented, then communication efficiency for modern devices is enhanced, but legacy applications experience communication inefficiency
Solution Approach 1:
The access point acts as a mediator that intercepts traffic from legacy applications, analyzes traffic characteristics, and routes traffic through appropriate network slices. This allows modern network infrastructure to optimize communication efficiency while maintaining reliable communication for legacy applications that cannot leverage network slicing natively.
Solution Approach 2:
The system changes the parameter of network traffic routing by dynamically selecting different network slices based on traffic characteristics, application type, and network conditions. This parameter change enables optimized routing for modern devices while providing reliable default routing for legacy applications, thereby improving overall communication efficiency without compromising legacy application performance.
Data Source
AI summary
Techniques are described herein for assigning a tag to untagged network traffic in order to allocate the network traffic to an appropriate network slice. In embodiments, the techniques may involve receiving network traffic that is untagged, determining information about the network traffic, identifying, based on the information about the network traffic, a set of attribute values associated with the network traffic, and assigning, based on the set of attribute values and based on configuration data, a tag to the network traffic. In embodiments, the network traffic is then allocated to a network slice associated with the assigned tag. In some embodiments, the techniques may further involve providing an indication of the tag and information about network traffic to at least one second computing device, and receiving, at the access point device from the at least one second computing device, updated configuration data.