An Overlay Management Strategy to Enhance Peer Stability in P2P Live Streaming Systems

Abstract

Peer-to-Peer (P2P) live streaming systems face persistent challenges due to dynamic peer participation, unpredictable churn, and fluctuating network conditions. This study introduces SPOM (Stable Peer Overlay Manager), a novel overlay management strategy based on preferential attachment, designed to enhance peer stability and network resilience. The approach prioritizes high-degree nodes to strengthen connectivity, minimize service disruptions from peer turnover, and optimize resource utilization for continuous streaming. The proposed method was evaluated using the Gnutella P2P dataset within a Python-based simulation environment, leveraging the Network framework. Key performance metrics including node degree distribution, clustering coefficient, and churn resilience demonstrated significant improvements. Results showed a network expansion of 10,000 additional edges, a 23.9% increase in average node degree (from 7.35 to 9.11), and enhanced local clustering, indicating a more robust overlay structure. Comparative analysis against random and cluster-based strategies revealed superior performance in reducing latency and maintaining fault tolerance during streaming sessions. These findings highlight the efficacy of structured, preference-driven overlay management in real-world P2P systems. The study contributes actionable insights for decentralized media delivery, offering scalable solutions to improve Quality of Service (QoS) in dynamic environments. Future research directions include adaptive enhancements via machine learning and deployment in heterogeneous and mobile networks to further strengthen resilience under high churn.