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Supporting efficient keyword-based file search in peer-to-peer file sharing systems

机译:支持对等文件共享系统中基于关键字的有效文件搜索

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Peer-to-peer (P2P) computing has become a popular distributed computing paradigm thanks to the abundant computing power of modern desktop workstations and widely available network connectivity. Although P2P file sharing provides a scalable alternative to conventional server-based approaches, providing efficient file search in a large-scale dynamic P2P system remains a challenging problem. We propose a set of mechanisms to provide a scalable keyword-based file search in distributed hash table (DHT) based P2P systems. Our proposed architecture, called keyword fusion, balances unfair storage consumptions at peers and transforms users' queries to contain focused search terms. Through trace-driven simulations, we show that keyword fusion can reduce the storage consumption of the top 5% most loaded nodes by 50% and decrease the search traffic by up to 67%, even in a modest scenario of combining two keywords.
机译:对等(P2P)计算已成为流行的分布式计算范例,这得益于现代台式机工作站的强大计算能力和广泛可用的网络连接性。尽管P2P文件共享为传统的基于服务器的方法提供了可伸缩的替代方法,但是在大规模动态P2P系统中提供有效的文件搜索仍然是一个具有挑战性的问题。我们提出了一套机制,可在基于分布式哈希表(DHT)的P2P系统中提供可扩展的基于关键字的文件搜索。我们提出的称为关键字融合的架构可平衡对等点之间的不公平存储消耗,并将用户的查询转换为包含重点搜索字词。通过跟踪驱动的模拟,我们表明即使在合并两个关键字的情况下,关键字融合也可以将负载最高的5%节点的存储消耗减少50%,并将搜索流量减少多达67%。

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