Edge Computing via Intermediate Data Extraction in Disaggregated RAN
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Solution Overview
Problem
Current edge computing technologies face high latency due to data traffic needing to pass through multiple stages of Radio Access Network (RAN) nodes, especially in disaggregated RAN deployments, where data processing occurs far from the user device, increasing overall delay.
Innovation Solution
Implementing edge computing over disaggregated RAN infrastructure through intermediate data extraction mechanisms that allow for low-latency processing closer to the data source, without requiring changes to existing communication protocols, by coordinating edge computing functions with RAN Intelligent Controllers to extract and process user data at intermediate RAN processing stages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data traffic passes through multiple stages of RAN nodes for processing, then network reliability and protocol compliance are improved, but latency increases significantly
Solution Approach 1:
The patent extracts user data from the intermediate RAN function node data flow before it continues through multiple processing stages. By taking out the user data at an intermediate point and forwarding it directly to the edge compute node, the system maintains protocol compliance (data still passes through all RAN stages) while eliminating unnecessary transmission delays for edge computing workloads.
Solution Approach 2:
The patent introduces an intermediary data extraction and forwarding mechanism between the RAN function node and the edge compute node. This intermediary system monitors the data flow, identifies user data destined for edge computing, and creates a direct transmission path that bypasses the traditional multi-stage RAN processing route, thereby reducing latency while maintaining network reliability.
2Adaptability or versatility
If edge compute nodes are placed far from user devices in disaggregated RAN deployments, then network flexibility and scalability are improved, but processing speed deteriorates
Solution Approach 1:
The patent segments the data flow into two paths: one for traditional RAN processing (maintaining network flexibility) and one for edge computing (optimizing processing speed). By segmenting the user data extraction and creating a dedicated direct path to edge compute nodes, the system achieves both geographical distribution benefits and low-latency processing.
3Loss of time
If intermediate data extraction is implemented in disaggregated RAN, then latency is reduced, but system complexity increases
Solution Approach 1:
The patent implements a universal data extraction mechanism at the RAN function node that can handle both traditional RAN traffic and edge computing traffic through a single integrated system. The extraction point is designed to work with existing RAN protocols and interfaces, adding edge computing functionality without requiring separate dedicated infrastructure, thereby limiting the increase in system complexity.
Data Source
AI summary
The present disclosure describes edge computing over disaggregated radio access network (RAN) infrastructure through dynamic edge data extraction. Edge data is extracted at intermediate stages of RAN processing, provided to edge compute functions, and inserted back into the RAN processing pipeline. These mechanisms allow for the processing of edge data traffic much closer to the data source than existing approaches, which decreases the overall latency and delay. Additionally, these mechanisms do not require changes to already existing network protocols, allowing for non-complex adoption and implementation.