## 6 Discussion
More critically, in traditional centralized architectures, server failures (especially cloud server crashes) can lead to catastrophic system-wide service disruptions affecting all connected users, with recovery potentially requiring tens of minutes to hours of manual intervention, during which the entire video service remains completely unavailable. By contrast, our decentralized approach fundamentally redefines fault recovery through dynamic chain reconstruction capabilities. When any node fails, the system quickly reroutes transmission paths by establishing new direct connections among remaining operational nodes, automatically bypassing failed components. This architecture eliminates the \"all-or-nothing\" failure mode inherent to centralized systems, as the impact of any node failure is limited to downstream connections and can be rapidly restored via self-healing mechanisms. More importantly, since no central server is responsible for actual media relaying, the system does not inherit the critical vulnerabilities associated with centralized architectures, ensuring predictable and minimal recovery times while maintaining near-continuous service availability, even in scenarios involving multiple simultaneous node failures. Furthermore, unlike traditional streaming services that rely on expensive server infrastructure and face high-concurrency bandwidth bottlenecks, our P2P architecture distributesthe load across the entire chain, significantly reducing both capital and operational expenditures. The system's low performance requirements for individual nodes enable seamless integration of various devices--including those with limited processing power and bandwidth--providing flexibility and cost-effectiveness that make it better suited for a wide range of applications. Due to the low requirements for individual node performance of the proposed system, it can easily incorporate a wide range of devices, including those with limited processing power and bandwidth. Some devices with extremely low power consumption and price, such as N100 or old Celeron(r) PCs, can be seamlessly integrated into the streaming network, providing flexibility and cost-effectiveness. The power and performance consumption of the system are also significantly lower than traditional RTMP-based architectures, which often require high-performance servers and dedicated hardware to handle the load and very powerful network devices with high bandwidth, high power consumption, and certainly high cost. Moreover, the dedicated servers require significant investment in infrastructure and maintenance, which is a barrier to entry for many potential users, such as small businesses or institutions, especially in developing regions or rural areas. In contrast, the proposed system can achieve similar or even better performance with much lower hardware requirements, making it more accessible and affordable for a wider range of applications. To contextualize these results, we benchmarked against the study _The Design and Implementation of Campus Network Streaming Media Live Video On-Demand System Based on Nginx and FFmpeg_[63]. That TCP-bound, server-centric architecture aggregates every viewer at a stateful Nginx hub and scales upstream bandwidth linearly with sites, yielding \(>800\) ms added glass-to-glass delay and elevated jitter once concurrent venues exceed five. By contrast, our hop-wise SRT chain, based upon UDP, halves head-end bandwidth at eight sites, sustains \(<400\) ms total latency, and preserves AES-encrypted reliability without introducing single points of failure. The evidence therefore supports chain-aware, server-light broadcasting as a scalable, cost-efficient alternative for future multi-venue deployments (Figure 13).