## 6 Discussion
These findings underscore the value of redundant paths, adaptive buffering, and selective retransmission for maintaining perceptual quality in volatile WANs. Although our scheme exhibits a roughly linear increase in end-to-end latency with chain length, this is fundamentally more predictable and manageable than traditional RTMP-based architectures. In large-scale streaming scenarios, RTMP delay often grows faster than linearly due to bandwidth bottlenecks and server overload, resulting in much higher and less stable latencies. This highlights the scalability and robustness advantages of our decentralized SRT chain approach (Figure 10). Figure 9: VMAF scores under varying network conditions. Furthermore, we evaluated the system under adverse network conditions and compared it with a conventional RTMP-based approach. It is worth noting that, under traditional centralized RTMP architecture, poor network conditions, low-end network adapters, and underpowered CPUs/GPUs make it nearly impossible to sustain a broadcast stream. Severe stuttering, highly unstable frame rates, and frequent playback freezes are observed, resulting in the stream always being stuck or advancing frame by frame. In such cases, quantitative metrics like frame rate lose practical significance, as the system hardly maintains continuous playback. However, in the proposed decentralized chain-based architecture, even under the same adverse conditions, the system can still deliver a stable stream with an acceptable quality. The extremely high performance of the SRT protocol, combined with the chain-based architecture, allows the system to maintain a stable stream even in challenging environments. This is a significant advantage over traditional centralized RTMP-based systems, which struggle to deliver reliable performance under similar conditions (Figure 11). The comparative evaluation of packet loss handling mechanisms revealed significant performance advantages of SRT's adaptive strategies over traditional ARQ approaches. Figure 11: Comparison of video frame quality between the proposed scheme and the RTMP-based baseline. **(a)** The 1 st frame of decentralized SRT chain streaming; **(b)** The 1 st frame of the traditional RTMP multicast; **(c)** The 2 nd frame of decentralized SRT chain streaming; **(d)** The 2 nd frame of the traditional RTMP multicast. Figure 10: Comparison of latency: decentralized SRT chain vs. traditional RTMP protocol. Under controlled packet loss conditions, three key findings emerged that demonstrate the superiority of SRT's intelligent packet handling. Figure 12 illustrates the latency impact of different packet loss handling strategies under varying loss rates. The default ARQ mechanism exhibits exponential latency growth as packet loss increases, with end-to-end delays exceeding 2000 ms at 5% loss rate due to head-of-line blocking. In contrast, SRT's selective ARQ maintains substantially lower latency increases, with delays remaining below 800 ms even at 10% packet loss. The SRT adaptive drop mechanism demonstrates the most resilient performance, maintaining near-constant latency by intelligently discarding packets that would violate temporal constraints. Quantitative analysis of playback continuity revealed striking differences in user experience quality. Traditional ARQ resulted in frequent and prolonged freeze events, with average freeze durations of 850 ms at 2% packet loss and complete playback breakdown beyond 5% loss. SRT's selective retransmission reduced freeze frequency by 73% and average freeze duration by 68%, maintaining acceptable viewing experience even under severe network conditions. The adaptive drop mechanism virtually eliminated freeze events by gracefully degrading quality rather than stalling playback. Table 2 presents comprehensive performance metrics across different packet loss scenarios. The data clearly demonstrates SRT's superior efficiency in managing network impairments.