The Survey of Developing Peer-to-Peer (P2P) Multimedia Algorithm for Live Streaming to Enhance QoS in Cloud Environment

In this survey, I examined the latest developments in Peer-to-Peer (P2P) multimedia algorithms, particularly how they enhance live streaming performance when integrated with modern technologies like cloud computing, artificial intelligence [AI], block chain, 5G, and edge computing. My focus is on how these technologies work together to address key challenges in Quality of Service (QoS), scalability, latency, and system reliability. I reviewed a range of current system architectures, especially hybrid models that combine P2P with cloud or content delivery networks (CDNs). These setups are evaluated based on how well they manage real-time resources, deliver adaptive video quality, ensure secure content sharing, and make efficient use of peer contributions. I also studied algorithms driven by reinforcement learning, trust-based decentralization, and edge-level computation. From this analysis, I found that hybrid systems offer a strong balance between the stability of cloud services and the flexibility of peer networks. AI plays a valuable role in adapting to changing conditions, while block chain helps secure content delivery although it may sometimes slow the system down. The combination of 5G and edge computing shows real promise in lowering delays and improving real-time responsiveness. However, several challenges remain. These include unpredictable peer behavior, fluctuating network quality, high implementation costs, and persistent security concerns in decentralized environments. In conclusion, I point to future research opportunities focused on building smarter, more reliable, and highly scalable streaming solutions. By connecting multiple emerging technologies, this work provides meaningful guidance for researchers and developers aiming to advance the next generation of decentralized live streaming platforms.