Telecommunications Network Reconfiguration via Raw Data Extraction
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Solution Overview
Problem
Telecommunications networks face challenges in maintaining transparency and managing dynamic, divergent environments due to limitations in traditional data sources and manual topology maintenance, which hinders effective fault detection and network automation across multiple layers of the OSI model.
Innovation Solution
A method and system that extract, convert, and store raw network data for parallel processing, making it available through APIs for fault detection and topology modeling, enabling identification of root causes and automated reconfiguration across multiple OSI layers without vendor or technology dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional data sources (SNMP, logs, KPIs) are used for network monitoring, then network status can be identified, but the data becomes vendor-specific and requires normalization which creates data format consistency, correlation, and synchronization problems
Solution Approach 1:
The patent extracts only the essential network status information from diverse data sources using standardized telemetry protocols, avoiding the need to process and normalize complete raw data sets. This extraction approach retrieves critical parameters while leaving vendor-specific details behind, thus reducing normalization complexity.
Solution Approach 2:
The patent implements a universal data collection framework that works across multiple vendors and technologies using standardized protocols. This multi-functional approach allows the same system to collect, process, and analyze network data from different sources without requiring vendor-specific normalization logic.
2Stability of the object's composition
If manual topology maintenance is performed, then network topology can be maintained, but it becomes difficult to maintain in dynamic and divergent networks
Solution Approach 1:
The patent performs preliminary actions by continuously collecting network data and pre-processing it into standardized formats before topology changes occur. This advance preparation ensures that when dynamic changes happen in the network, the topology can be updated automatically using the pre-processed data, reducing manual maintenance effort.
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor network status and automatically update topology information based on detected changes. This closed-loop approach allows the system to self-correct and maintain accurate topology information in dynamic networks without requiring manual intervention.
3Reliability
If traditional analytics tools are used with vendor-specific data sources, then fault detection can be performed, but the analytics cannot be transferred to other normalization layers and root cause identification requires manual knowledge
Solution Approach 1:
The patent changes the parameters of data collection by using standardized telemetry protocols that define uniform data formats, time intervals, and measurement units. This parameter standardization allows analytics models to process data from any vendor without reconfiguration, enabling transferability across different normalization layers while maintaining fault detection accuracy.
4Quantity of substance
If raw network data is collected and stored in proprietary formats, then data can be stored, but it cannot be leveraged to build topologies over multiple network layers
Solution Approach 1:
The patent segments the network data collection process into distinct layers corresponding to different OSI model levels. Each layer collects and standardizes data specific to its domain, allowing multi-layer topology construction without requiring handling of all raw data in a single proprietary format. This segmentation reduces format diversity complexity while preserving the quantity of collectable data.
Data Source
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AI summary
The present invention refers to a method to enable a (re-)configuration of a telecommunications network, the method comprising at least the following steps: - extracting, capturing and collecting (110) raw network data from at least one network function, - duplicating (120) the captured raw network data, - converting (120) the duplicated captured raw network data into a human readable format, - storing (120) the converted raw network data in a data storage, and - making (130) the stored raw network data available through at least one application programming interface for a further deployment for the (re-)configuration of the telecommunications network, - retrieving (131) via the at least one application programming interface at least a subset of the available raw network data, the subset being dependent on the further deployment, and - searching the retrieved raw network data for deployment specific indicators.