An efficient congestion control scheme for railway transport networks

Abstract

As the complexity of railway transmission network services continues to increase, burst traffic and the mixing of signaling have become significant challenges in congestion control. This paper presents a congestion control strategy based on the stochastic flow queue-controlled delay (SFQ-CoDel) algorithm, developed through an analysis of the traffic characteristics and operational demands of contemporary railway transmission networks. The scheme primarily integrates a random flow queue mechanism with a dynamic Hurst coefficient calculation method. The random flow queue employs hash mapping to distinguish data packets, thereby ensuring fair bandwidth allocation across active sub-flows. The dynamic computation of the Hurst coefficient, coupled with a minimum queue delay, formulates a packet loss strategy that effectively mitigates the effects of burst traffic. Experimental results indicate that the SFQ-CoDel algorithm excels in minimizing packet loss, enhancing throughput, and maintaining stable queue lengths, regardless of the load. Additionally, an analysis of parameter adjustability confirms that, even with the inclusion of the stochastic flow queue (SFQ) mechanism, the CoDel parameters consistently sustain optimal algorithm performance. Therefore, the proposed congestion control scheme provides a robust and adaptable framework for managing congestion within railway transmission networks.