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Popularity Adaptive Search In Hybrid P2p Systems

机译:混合P2p系统中的流行度自适应搜索

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In a hybrid peer-to-peer (P2P) system, flooding and DHT are both employed for content locating. The decision to use flooding or DHT largely depends on the population of desired data. Previous works either use local information only, or do not consider dynamic factors of P2P systems. In this paper, we propose a Popularity Adaptive Search method for Hybrid (PASH) protocol. By dynamically estimating the content popularity, PASH properly selects search methods so as to efficiently saves query traffic cost and response time. We evaluate PASH through synthetic and trace-driven simulations. The results show that PASH outperforms existing approaches and it also scales well.
机译:在混合对等(P2P)系统中,泛洪和DHT都用于内容定位。使用泛洪或DHT的决定很大程度上取决于所需数据的数量。以前的作品要么仅使用本地信息,要么不考虑P2P系统的动态因素。在本文中,我们提出了一种混合流行度自适应搜索(PASH)协议。通过动态估算内容的受欢迎程度,PASH可以正确选择搜索方法,从而有效节省查询流量成本和响应时间。我们通过综合和跟踪驱动的仿真来评估PASH。结果表明,PASH的性能优于现有方法,并且扩展性也很好。

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