## 5 Results  
Under the medium network condition, the 5-hop chain achieved an average VMAF score of 83.5, significantly outperforming the baseline system's 65.2. Even under the most adverse network setting (2 Mbps with 5% packet loss), the proposed system maintained VMAF scores above 72 (Figure 5). The cumulative PSNR drop across 8 hops was only 2.1 dB, decreasing from 42.3 dB at the source to 40.2 dB at the terminal node, indicating well-preserved visual fidelity across the chain. The package loss handling performance of SRT was evaluated under various network conditions, and the results are shown in Figure 6. As is shown, the SRT protocol's adaptive strategies significantly outperformed traditional ARQ mechanisms, particularly under high packet loss rates. Fault resilience was validated through a series of controlled fault injection tests. The system demonstrated robust self-healing capabilities, with an average recovery time of 12 s for a simulated 30 s power outage in some venues in the chain, a high loss spike broke the streaming continuity, or in a process crash, in a large-scale scenario. The standard deviation of recovery times across a single case was 1.2 s, which indicates that the recovery time is consistent and predictable across different fault scenarios and can be effectively managed by the system. On smaller scales, the values are much lower and the distinction is much  
Figure 5: Comparison of VMAF: decentralized SRT chain vs. traditional centralized RTMP protocol. less pronounced, thus not discussed. In small-scale experiments involving only three hops, the recovery time was 1.3 s with a standard deviation of 0.2 s, which is negligible. The self-healing algorithm successfully reconstructed the relay chain and resumed streaming without requiring manual intervention. Figure 7 illustrates the recovery time under different fault scenarios, demonstrating the system's resilience to both transient and persistent faults. As a comparison, the RTMP method cannot recover itself automatically after a crash, and the user has to manually restart the stream, which can take several minutes and requires communication between the venue and the server to re-establish the connection after the restart. The restart of the server requires manual intervention and usually takes several minutes, which is not acceptable for real-time video streaming applications. In contrast, the SRT-based system can automatically recover from faults and resume streaming within seconds, reducing over 90% of the time required for manual intervention. This capability is crucial for maintaining uninterrupted service in real-time applications such as live events, conferences, and educational broadcasts, saving not only time but also operational costs associated with manual recovery efforts. In addition to recovery behavior, delay performance was monitored to assess real-time delivery viability. The system demonstrated average end-to-end latencies of 523 ms and 695 ms for the 5-hop, 8-hop, and 20-hop chains, respectively, remaining within acceptable bounds for real-time interactive video. Jitter remained consistently below 15 ms across all hop lengths, ensuring smooth playback without buffer underruns. Furthermore, by specifying key SRT stream parameters such as latency tolerance and buffer size, we effectively controlled the maximum point-to-point delay, keeping per-device latency under 40 ms even in long relay chains. With a smaller buffer size, the latency can  
Figure 6: SRT packet loss handling performance under different loss rates. Figure 7: Recovery time under different fault scenarios. be reduced as a compromise between latency and reliability, which is particularly useful for applications requiring extreme real-time performance, such as live video streaming of competitive games, while other situations, like video conferencing, can tolerate higher latency but require extremely low jitter and packet loss.