防止 "搭便车 "的信誉驱动型点对点直播架构

Rashmi Kushwaha, Rahul Bhattacharyya, Yatindra Nath Singh
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摘要

我们提出了一种点对点(P2P)直播架构,旨在通过集成声誉系统来应对搭便车、恶意同行、流失和网络不稳定等挑战。所提出的算法通过声誉机制奖励利他主义的同行,惩罚搭便车者和恶意行为者,激励同行积极参与,同时阻止机会主义行为。为了管理同伴动态,该算法不断更新策略,并根据不断变化的邻居进行调整。该算法还针对闪存人群场景实现了请求-加入机制,允许源节点将请求委托给子节点,形成一个相互连接的树状结构,从而有效处理高需求并保持系统稳定。分散式信誉机制促进了 P2P 实时流媒体系统的长期可持续性。
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Reputation-Driven Peer-to-Peer Live Streaming Architecture for Preventing Free-Riding
We present a peer-to-peer (P2P) live-streaming architecture designed to address challenges such as free-riding, malicious peers, churn, and network instability through the integration of a reputation system. The proposed algorithm incentivizes active peer participation while discouraging opportunistic behaviors, with a reputation mechanism that rewards altruistic peers and penalizes free riders and malicious actors. To manage peer dynamics, the algorithm continuously updates the strategies and adjusts to changing neighbors. It also implements a request-to-join mechanism for flash crowd scenarios, allowing the source node to delegate requests to child nodes, forming an interconnected tree structure that efficiently handles high demand and maintains system stability. The decentralized reputation mechanism promotes long-term sustainability in the P2P live streaming system.
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