Core Simulation Tool for EPC Network Parameter Optimization
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Solution Overview
Problem
Current systems for managing software-defined networks, particularly in 5G environments, lack the ability to dynamically collect and analyze data from IoT sensors and RANs within the Evolved Packet Core (EPC), leading to incomplete network assessments and inefficient operations.
Innovation Solution
A Core Simulation Tool (CST) with a dynamic software-defined engine (SDE) is deployed within the EPC to collect data from IoT devices and RANs, create analytics environments, and dynamically adjust network parameters based on real-time analysis, enabling comprehensive network management and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a Core Simulation Tool with dynamic software-defined engine is deployed within the EPC to collect and analyze data from IoT sensors and RANs, then network performance and control are improved, but device complexity increases
Solution Approach 1:
The patent introduces a Core Simulation Tool (CST) with a dynamic software-defined engine as an intermediary component deployed within the EPC. This tool acts as a mediator between IoT sensors, RANs, and network management functions, collecting data from multiple sources and providing centralized analysis capabilities. The CST includes a data capture engine, simulation engine, and analytics environment that work together to process sensor data without requiring complex modifications to existing network infrastructure components.
Solution Approach 2:
The Core Simulation Tool is designed as a multi-functional platform that performs diverse network management tasks including data collection from IoT sensors and RANs, real-time simulation of network scenarios, analytics processing, and dynamic adjustment of network parameters. This universal tool consolidates multiple specialized functions into a single system, improving reliability while managing complexity through functional integration rather than proliferation of separate components.
2Measurement precision
If real-time data collection and analysis is implemented across the network, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring the Core Simulation Tool with simulation scenarios, analytics models, and decision-making rules before actual network operations. The simulation engine pre-processes potential network conditions and outcomes, creating a library of analyzed scenarios that can be quickly matched against real-time sensor data. This preparation work is done in advance, so when actual data collection occurs, the system can rapidly compare real measurements against pre-analyzed scenarios without performing full analysis in real-time.
Solution Approach 2:
The system establishes continuous feedback loops where analytics results from sensor data are fed back to adjust simulation parameters and refine measurement models. The CST monitors network performance metrics in real-time, compares them against simulation predictions, and uses the discrepancy feedback to improve measurement precision over time. This iterative feedback mechanism allows the system to maintain high accuracy while reducing the time required for each measurement cycle through learned optimization.
Data Source
AI summary
A device in an evolved packet core (EPC) which includes a processor and a memory. The processor effectuates operations including receiving from one or more devices residing within a customer premise equipment (CPE) portion of a telecommunications network, sensor data associated with one or more customers and in response to receiving the sensor data, generating a data request for an ecosystem status for the CPE portion of the telecommunications network. The processor further effectuates operations including obtaining customer information for the one or more customers and creating an analytics environment, using the customer information, for the one or more customers. The processor further effectuates operations including performing, within the analytics environment, analytics on the sensor data to determine a state of the CPE portion of the telecommunications network for the one or more customers and in response to performing analytics on the sensor data, optimizing the telecommunications network.