Edge Data Filtering in Cellular Network Cloud Architecture
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
As telecom networks expand, managing and processing the vast amounts of operating data from cell sites becomes increasingly challenging, requiring efficient methods to reduce data volume while maintaining readability and accuracy.
Innovation Solution
The implementation of advanced analytics and machine learning algorithms at the edge of the network, combined with a distributed architecture that includes central and private clouds, enables the extraction of valuable insights from large data sets without storing all raw data. This approach filters, corrects, and formats data to derive meaningful information while reducing storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all raw operating data from cell sites is stored and processed centrally, then complete data availability is achieved, but storage requirements and data management complexity increase exponentially
Solution Approach 1:
The system performs preliminary data filtering, correction, and formatting at edge locations (cell sites and local data centers) before data is transmitted to the central cloud. This advance processing reduces the volume of raw data that needs to be stored and transmitted, while ensuring that only relevant, corrected data reaches the central system, thus maintaining data availability while reducing storage requirements
Solution Approach 2:
The patent divides the data processing system into multiple segments: edge devices at cell sites, local data center processing, and central cloud processing. Each segment handles specific processing tasks, with edge devices performing initial filtering and correction, local data centers performing additional processing, and the central cloud performing aggregate analysis. This segmentation allows data to be processed in stages, reducing the burden on any single system and minimizing the volume of data that must be stored centrally
2Reliability
If extensive raw data is collected from all cell sites, then comprehensive network monitoring is achieved, but data processing and management difficulty increases
Solution Approach 1:
Data correction and filtering are performed in advance at edge locations before data leaves the cell site or local data center. This preliminary action ensures that data is corrected for known errors and filtered for relevance before entering the central management system, reducing the complexity of data processing required at the central level while maintaining comprehensive monitoring capability
Solution Approach 2:
Local data centers and edge processing systems act as intermediaries between cell sites and the central cloud. These intermediaries perform initial data correction, filtering, and aggregation, reducing the complexity of data that reaches the central management system. The intermediary layer handles the bulk of data processing complexity, allowing the central system to focus on higher-level analysis and decision-making
3Quantity of substance
If data is filtered and processed at the edge before transmission, then storage requirements are reduced, but data processing time may increase
Solution Approach 1:
Data filtering and correction are performed in advance at edge locations using lightweight processing that can operate in near-real-time. This preliminary action reduces data volume before transmission, and because the processing occurs at the source using locally available computing resources, it does not significantly increase overall processing time. The reduced data volume actually decreases transmission time to the cloud, offsetting the edge processing time
Solution Approach 2:
The system maintains continuous data processing and transmission operations without interruption. Edge devices continuously filter and correct data as it is generated, and the reduced data volume enables continuous transmission to the cloud without batching delays. This continuous operation ensures that data processing time is minimized while achieving significant storage reduction through ongoing data filtering and aggregation
Data Source
AI summary
A cellular network having radio access network (RAN) nodes where each RAN node includes (i) a central unit (CU) that resides on a public cloud of the cellular network, (ii) a distributed unit (DU) that resides on a private cloud of the cellular network such that the DU is in communication with the CU on the public cloud of the cellular network, and (iii) a radio unit (RU) under control of the DU. The cellular network also has network repository functions (NRFs) that are distributed on the cellular network and reside on at least the public cloud of the cellular network where the NRFs control operation of cell sites and local data centers (LDCs) on the cellular network. The network also has processors configured to control data collection edge applications residing with the NRFs that are distributed on the cellular network.