Roadside Node Data Filtering for V2X Congestion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing roadside network nodes face inefficiencies in processing and transmitting data due to duplicate information and high processing loads, leading to increased effort and potential congestion in communication channels, especially in Vehicle-to-Everything (V2X) networks.
Innovation Solution
A roadside network node equipped with both cell-supported and ad-hoc radio modules, capable of determining similarity values between data entities received through different channels, aggregates and filters data to prevent duplicate transmissions, thereby reducing processing effort and congestion by selectively providing only new or different content to higher layers or channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the roadside network node receives and processes all data entities from multiple radio channels, then complete information is available for transmission, but processing load and channel congestion increase significantly
Solution Approach 1:
The system performs preliminary comparison and similarity assessment of data entities before full processing and transmission. By evaluating similarity values in advance, the system identifies and filters duplicate data entities, preventing unnecessary processing and transmission of redundant information while maintaining information completeness.
Solution Approach 2:
The system extracts and removes duplicate data entities from the received data stream by comparing similarity values. Only data entities with sufficient差异性 (difference) are selected for further processing and transmission, effectively separating useful unique information from redundant duplicates.
2Reliability
If duplicate data entities are transmitted through multiple radio channels, then data redundancy provides backup transmission paths, but channel congestion and network inefficiency increase
Solution Approach 1:
The system extracts and eliminates duplicate data entities by comparing similarity values across different radio channels. By removing redundant duplicates before transmission, the system prevents channel congestion while maintaining transmission reliability through selective propagation of unique data entities.
Solution Approach 2:
Instead of transmitting all received data entities through all channels, the system applies partial action by selectively transmitting only those data entities that meet the similarity threshold criteria. This reduces unnecessary transmissions that would cause congestion while maintaining sufficient redundancy for reliability.
3Loss of information
If all received data entities are provided to higher layer functions, then no information is lost, but processing effort and computational resources are wasted on duplicates
Solution Approach 1:
The system extracts and removes duplicate data entities by comparing similarity values before providing data to higher layer functions. This extraction process eliminates redundant processing while ensuring that all unique information is preserved and transmitted upward in the protocol stack.
Solution Approach 2:
The system performs preliminary filtering and similarity assessment before data entities are provided to higher layer functions. By conducting this preliminary action, the system prevents wasteful processing of duplicates at higher layers while maintaining complete information availability for unique data entities.
Data Source
Figure 1
Figure 2a
Figure 2b
AI summary
According to a further aspect a method to operate a road-side network node in a cell-supported radio communications network and in an adhoc radio communications network is provided. The method comprises: receiving (802) a plurality of first data entities via a sidelink radio channel of the cell-supported radio communications network; receiving (804) a plurality of second data entities via an adhoc radio channel of the adhoc radio communications network; determining (806) a similarity value for at least a pair of data entities from the plurality of first and second data entities; and providing (808) the pair of data entities in dependence on the similarity value.