Network Entity KPI Data Filtering for Bandwidth Reduction

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Solution Overview

Problem

The existing systems face challenges in efficiently handling the enormous amount of Key Performance Indicator (KPI) data generated by network elements (NEs) in telecommunication networks, leading to high storage costs and latency in processing, which can result in delayed identification of performance degradations and potential loss of critical events during high network loads.

Innovation Solution

A method and network entity that generate a file containing only the most significant KPI data points by removing insignificant data points based on a dynamic threshold value defined using a machine learning model, thereby reducing file size and improving transfer speed and storage efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If all KPI data points are transferred and stored, then complete monitoring information is available, but storage space and bandwidth usage become enormous

Engineering Contradiction:

Improvemonitoring information completenessVSAvoidstorage space

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent extracts only the significant KPI data points that exceed a dynamically determined threshold from the complete set of KPI data. By removing insignificant data points through statistical analysis and threshold-based filtering, the system retains essential monitoring information while dramatically reducing the quantity of stored data.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent changes the parameter of data significance by introducing a dynamic threshold value that adapts based on historical data statistics. This threshold dynamically separates significant from insignificant data points, allowing the system to maintain monitoring reliability while reducing storage requirements through parameter-based filtering.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If all KPI data points are transferred, then complete performance monitoring is achieved, but bandwidth usage and transfer time increase significantly

Engineering Contradiction:

Improveperformance monitoring completenessVSAvoidbandwidth usage

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies partial action by transferring only a subset of KPI data points rather than all data. By using threshold-based filtering to select only significant data points for transfer, the system achieves sufficient monitoring coverage with reduced bandwidth consumption and faster transfer times.

Inventive Principle:

Principle #16Partial or excessive action

3Quantity of substance

If compression techniques are applied to reduce data size, then storage and transfer costs decrease, but response time increases

Engineering Contradiction:

Improvedata sizeVSAvoidresponse time

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The patent performs preliminary action by filtering and selecting significant data points at the source before transfer. By applying threshold-based filtering and statistical analysis at the NE level before data leaves the source, the system reduces data size without requiring time-consuming compression/decompression operations during transfer or processing.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent substitutes mechanical compression techniques with a smarter filtering mechanism based on statistical analysis and dynamic thresholds. This approach replaces time-consuming compression algorithms with more efficient threshold-based selection, achieving data reduction without the computational overhead of traditional compression methods.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Productivity

If dynamic threshold filtering is applied to remove insignificant data, then file size and processing load are reduced, but data accuracy may be affected

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidKPI data accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements feedback by continuously analyzing historical KPI data to dynamically adjust the threshold value. The system uses statistical measures (mean, standard deviation) from historical data to adaptively determine what constitutes a significant change, ensuring that the filtering process maintains accuracy while improving processing efficiency.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12244472B2Method and network entity for handling KPI PM data

Publication Date: 2025.03.04 SAMSUNG ELECTRONICS CO LTD

AI summary

The embodiments herein provide a method for reducing KPI data. The disclosed technique is used to reduce insignificant KPI data generated by network entities (NEs) such as Radio Access Network (RAN) or element management system (EMS)/network management system (NMS). Further, the method includes determining a threshold value for each KPI data to determine significance of the KPI data and uses the threshold value to reduce the KPI data in a file. Further, the method includes utilizing a network bandwidth (e.g., control plane traffic load) and a storage space in the EMS/operations support system (OSS) efficiently and helps operators of the EMS/OSS to identify a network KPI deterioration in near real time.