Enhanced congestion control in transmission control protocol using harmonic red panda optimisation for heterogeneous networks

Transmission Control Protocol (TCP) plays a crucial role in daily activities, from accessing emails to internet browsing. To ensure consistent and secure data delivery while minimising data loss, innovative mechanisms are essential. While TCP performs well in conventional environments with traditional Congestion Control (CC) approaches, achieving high utilisation, stability and fairness in heterogeneous networks remains a challenge. This research introduces the Harmonic Red Panda Optimisation (HRPO) method for CC in TCP, a novel approach combining harmonic analysis with Red Panda Optimisation (RPO). Initially, TCP system model is simulated and then, a designed TCP algorithm performs the following steps. Firstly, Congestion Window (CWND) is initialised and next, estimation of bandwidth (BW) is carried out. Thereafter, computation of CC factor is done and finally, convergence factor is estimated. The estimation of convergence factor is performed by HRPO. Experimental results demonstrate that HRPO achieves significant improvements, including a maximal goodput of 1951.352 Mbps, throughput of 1587.167 Mbps and a Signal to Interference Noise Ratio (SINR) of 39.595 dB. These results highlight the superiority of HRPO in delivering higher performance and stability compared to existing CC methods, particularly in heterogeneous network environments.