## 2 Related Work
### Decentralized Crowdsourced Video Streaming Systems  
Decentralized crowdsourced video streaming systems represent a crucial application of P2P technology in the User-Generated Content (UGC) domain. Unlike traditional content delivery networks, crowdsourced systems face unique technical challenges such as high content source heterogeneity, inconsistent data quality, and complex real-time synchronization [30]. At the commercial level, major live streaming platforms like Twitch and YouTube Live, while providing user-friendly service interfaces, fundamentally rely on large-scale cloud computing infrastructures, leading to high operational costs and inherent centralization risks. In recent years, blockchain-based decentralized streaming platforms such as Livepeer [26] and Theta Network have begun exploring truly decentralized solutions, although these nascent systems still face technical bottlenecks concerning real-time performance and scalability. In academic research, [PERSON] and [PERSON] [30] proposed a distributed multi-source video acquisition and distribution system specifically tailored for large-scale events. Its technical architecture comprised node discovery and routing mechanisms based on the Kademlia Distributed Hash Table (DHT), a Bitswap protocol-driven content exchange algorithm for efficient video segment distribution, and an FFmpeg-driven multi-source video synthesis engine supporting real-time multi-view stitching. Experimental results demonstrated the system's effectiveness in handling multiple concurrent video streams while providing a positive user experience.  
WebRTC technology offers an alternative and increasingly viable technical pathway for decentralized video transmission [18]. Research by [PERSON] et al. indicates that WebRTC-based pure P2P video systems can operate stably on resource-constrained embedded devices. Their key advantages include direct end-to-end communication without server intermediation, built-in NAT traversal mechanisms that simplify network configuration, and adaptive encoding technology ensuring transmission quality across varying network conditions. Performance evaluations of such systems typically show excellent CPU utilization, memory consumption, and bandwidth efficiency.  
Beyond core transmission, reputation management mechanisms play a vital role in enhancing the stability and efficiency of decentralized systems. The ReputeStream system [7] effectively mitigates node free-riding behavior by introducing a Bayesian theory-based reputation evaluation algorithm. This system employs a multi-layer overlay architecture, strategically deploying high-reputation nodes closer to content sources, which significantly improves the overall network's transmission efficiency and stability [29]. Despite substantial advancements in decentralized crowdsourced video systems, particularly with innovative solutions for reputation mechanisms, node collaboration, and content scheduling [29], several key challenges persist in practical large-scale deployments. These include a current lack of unified Quality of Service (QoS) guarantees, making it difficult to maintain a consistent video experience across heterogeneous networks and devices. Moreover, frequent node online/offline behavior leads to unstable system topologies and unreliable transmission links. Additionally, as the number of participating nodes grows, achievingefficient task coordination and link maintenance while preserving decentralization becomes increasingly complex. It is specifically to address these issues that this paper proposes a chain-structured transmission architecture. This design simplifies inter-node connection relationships through topological design and introduces lightweight fault detection and recovery mechanisms, thereby enhancing link stability and service continuity while ensuring system scalability. This offers a novel technical pathway for building efficient and reliable P2P multi-venue real-time broadcasting systems.