## 6 Discussion
Particularly noteworthy is the dramatic reduction in buffer overflow events, where SRT's adaptive mechanisms reduce overflow rates by an order of magnitude compared with traditional ARQ. This improvement directly translates to more stable playback and reduced memory consumption on resource-constrained relay nodes. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Loss Handling** & **Loss Rate** & **Avg Latency (ms)** & **Freeze Events/min** & **VMAF Score** & **Buffer Overflow (\%)** \\ \hline \multirow{3}{*}{Default ARQ} & 1\% & 485 & 2.3 & 78.2 & 8.5 \\  & 2\% & 892 & 5.7 & 65.1 & 18.2 \\  & 5\% & 2156 & 12.4 & 42.3 & 35.7 \\ \hline \multirow{3}{*}{SRT Selective ARQ} & 1\% & 312 & 0.8 & 84.6 & 2.1 \\  & 2\% & 421 & 1.9 & 81.2 & 4.3 \\  & 5\% & 687 & 3.8 & 75.8 & 8.9 \\ \hline \multirow{3}{*}{SRT Adaptive Drop} & 1\% & 298 & 0.1 & 83.1 & 0.3 \\  & 2\% & 315 & 0.3 & 79.4 & 0.8 \\ \cline{1-1}  & 5\% & 356 & 0.7 & 72.6 & 1.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Packet Loss Handling Performance Comparison. Figure 12: Latency impact comparison across different packet loss handling mechanisms. The retransmission efficiency analysis, calculated using Equation (6), revealed that SRT's selective ARQ achieved efficiency values of 0.89-0.94 across all tested conditions, compared with 0.45-0.67 for traditional ARQ under identical network conditions. This 50-100% improvement in efficiency stems from SRT's ability to avoid unnecessary retransmissions of time-expired packets and its intelligent prioritization of critical frame data. Under burst loss patterns, which simulate realistic network congestion events, SRT's advantages became even more pronounced. While traditional ARQ experienced cascading delays due to multiple consecutive packet losses, SRT's Forward Error Correction (FEC) integration enabled recovery without retransmission for up to three consecutive lost packets. This capability proved crucial for maintaining service quality during transient network congestion events common in WAN deployments. The experimental validation confirms that SRT's enhanced packet loss handling mechanisms provide substantial improvements in latency consistency, playback continuity, and resource utilization compared with traditional ARQ approaches. These findings support the theoretical advantages of selective retransmission and adaptive dropping strategies in real-time video streaming applications, particularly in challenging network environments where maintaining temporal constraints is paramount. Moreover, when the count of devices increases, the proposed system can still maintain a stable stream with acceptable quality. Even starting with a quite poor performance device like the Intel(r) N100 mini PC, the system can still deliver a stable stream with acceptable quality. However, in the traditional RTMP-based centralized architecture, as a comparison, the performance of the system is highly dependent on the performance of the server and the number of viewers, and under such extreme conditions with heavy pressure, the server is unable to handle the load, resulting in total failure of the stream. This highlights the robustness and scalability of the proposed decentralized chain-based architecture, which can effectively handle large-scale streaming scenarios without being bottlenecked by a single server's performance. Compared with traditional centralized streaming architectures, our decentralized chain-based system demonstrates significant advantages in fault recovery and service continuity. Traditional cloud service providers typically experience cold start delays ranging from 5 to 30 s, and system failures require complete session reconstruction. In contrast, our system achieves recovery times of approximately 10 s (in some cases even less than 2 s) through intelligent self-healing mechanisms.