Private Train Network Congestion Control via Predictive RSU Assistance
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Solution Overview
Problem
The existing decentralized congestion control (DCC) mechanism in private train networks is sub-optimal due to its inability to efficiently manage bursty communication traffic and uneven resource utilization across the network, leading to reduced overall system performance.
Innovation Solution
A method and system that utilize an application server to aggregate congestion control information from multiple road side units (RSUs), predict congestion status, and provide assistance information to RSUs to coordinate decentralized congestion control, thereby enhancing the overall network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If decentralized congestion control (DCC) is implemented at each RSU independently, then each RSU can manage its own congestion locally, but the overall system performance deteriorates due to inability to coordinate resource usage across the network
Solution Approach 1:
The patent introduces an application server as an intermediary that collects congestion control information from multiple RSUs, predicts congestion status, and provides assistance information back to RSUs. This mediator enables coordinated congestion control across the network while preserving the decentralized operational structure of individual RSUs.
Solution Approach 2:
The patent implements a feedback mechanism where RSUs report congestion control information (CBR and CR) to the application server, which then provides assistance information back to RSUs based on predicted congestion status. This closed-loop feedback enables dynamic coordination of congestion control across the network.
2Reliability
If DCC limits each RSU's channel occupancy independently, then fairness is improved, but system efficiency deteriorates when traffic is bursty or unevenly distributed
Solution Approach 1:
The patent makes the congestion control parameters dynamic by using prediction of future congestion status to provide assistance information to RSUs. The CRlimit is adjusted based on predicted CBR and current CR, allowing the system to adapt to bursty traffic patterns and uneven resource distribution while maintaining fairness.
Solution Approach 2:
The patent performs preliminary congestion status prediction before making congestion control decisions. The application server predicts future congestion status based on current CBR and CR values, and provides assistance information in advance, allowing RSUs to proactively adjust their transmission parameters to avoid congestion while maintaining efficient resource utilization.
3Speed
If CRlimit is set based on current CBR measurement, then immediate congestion response is achieved, but future congestion bursts are not prevented
Solution Approach 1:
The patent performs preliminary congestion status prediction based on current CBR and CR measurements before providing assistance information to RSUs. This predictive approach allows the system to prepare for future congestion bursts in advance, enabling RSUs to adjust their transmission parameters proactively rather than reactively, thus preventing congestion before it occurs while maintaining fast response capability.
Data Source
AI summary
A method for controlling congestion of a private train network, which comprises a plurality of road side units and each connected to an application server, wherein each of said plurality of road side units is adapted to establish sidelink communications, comprising:aggregating congestion control information from a subset of said a plurality of road side units and railway application information by the application server;predicting congestion status of each of the subset of said a plurality of road side units by the application server based on the aggregated congestion control information and the railway application information;calculating and providing assistance information to the subset of said a plurality of road side units by the application server based on the predicted congestion status; andperforming Decentralized Congestion Control by the subset of said a plurality of road side units based on the assistance information.