V2X Edge Server Configuration via Digital Twin Simulation
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Solution Overview
Problem
Existing solutions for designing and configuring edge servers and roadside units in Vehicle-to-Everything (V2X) networks lack standardization, leading to network congestions due to redundant data transmission and limited storage and computational capacity, especially during adverse conditions like traffic accidents or congestions.
Innovation Solution
A computer program product that executes simulations to generate formally verified configuration data for network elements, including edge servers, using digital twin simulations and assume-guarantee contracts to optimize network configurations and ensure Quality-of-Service (QoS) under various conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple vehicles transmit similar data to edge servers during traffic accidents or congestions, then data transmission volume increases, but network congestion occurs due to redundant information
Solution Approach 1:
The system extracts and identifies redundant information from multiple vehicle data transmissions by comparing data content and identifying similarities. Edge servers filter out duplicate data packets representing the same traffic scene or accident conditions, keeping only unique information for processing and storage.
Solution Approach 2:
The system merges data from multiple vehicles by consolidating redundant information into single representative data packets. When multiple vehicles transmit similar traffic scene data, the system combines these transmissions into one unified data set, reducing overall transmission volume while maintaining data completeness.
2Speed
If edge servers store and process local data, then response time improves, but storage capacity and computational power are limited
Solution Approach 1:
The system segments data storage and processing across a hierarchical architecture: edge servers handle local real-time processing for immediate response, while cloud servers provide centralized storage for historical data and complex computations. This segmentation allows edge servers to maintain fast response times without being burdened by large-scale storage requirements.
Solution Approach 2:
The system performs preliminary data processing and filtering at the edge server level before data is transmitted to cloud servers. By pre-processing data locally to extract only essential information, the system reduces the computational burden on both edge and cloud servers, optimizing overall system capacity utilization.
3Adaptability or versatility
If edge servers are configured locally for each Area of Coverage, then service localization improves, but standardized configuration methods are lacking
Solution Approach 1:
The system implements a universal configuration framework that can be applied across multiple edge servers serving different Areas of Coverage. Standardized configuration templates define common parameters for data collection, processing, and transmission, while allowing local customization for region-specific requirements. This enables consistent deployment practices across diverse locations.
Solution Approach 2:
The system applies local quality by allowing each edge server to be configured with location-specific parameters while maintaining overall architectural consistency. Each Area of Coverage can customize data priorities, transmission thresholds, and processing rules based on local traffic patterns and requirements, while following standardized configuration methodologies.
Data Source
AI summary
The disclosure includes embodiments for designing and configuring network elements for a Vehicle-to-Everything (V2X) network. A method includes executing a set of simulations which is operable to generate configuration data that describes a configuration for a set of network elements that is formally verified. The set of network elements is included in the V2X network. The method includes configuring the set of network elements consistent with the configuration data.