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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >MTAF: An Adaptive Design for Keyword-Based Content Dissemination on DHT Networks
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MTAF: An Adaptive Design for Keyword-Based Content Dissemination on DHT Networks

机译：MTAF：DHT网络上基于关键字的内容分发的自适应设计

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摘要

Beyond offering the widely used keyword search function, many peer-to-peer systems nowadays support the subscription function. For example, Vuze allows users to create subscription filters based on the keyword search. Given the subscription, episodic or related content will be delivered to the users whenever new episodes are available. Unfortunately, these applications suffer from the downsides, for example, high network traffic in the nodes maintaining popular terms. In this paper, we propose the MTAF mechanism to overcome the issues. The key of MTAF is to carefully select a subset of terms without incurring false negatives and to forward the content item toward the home nodes of such selected terms for low content forwarding cost. Experimental results based on real datasets indicate that the proposed solutions are efficient compared to existing approaches. In particular, the similarity-based replication of filters is shown to mitigate the effect of hot spots that arise due to the fact that some document terms are substantially more popular than the others.
机译：除了提供广泛使用的关键字搜索功能之外，当今许多对等系统还支持订阅功能。例如，Vuze允许用户基于关键字搜索创建订阅筛选器。给定订阅后，只要有新的剧集可用，就会向用户传递情景或相关内容。不幸的是，这些应用遭受不利影响，例如，节点中的高网络流量保持流行术语。在本文中，我们提出了MTAF机制来克服这些问题。 MTAF的关键是仔细选择术语的子集而不会引起误报，并以较低的内容转发成本将内容项转发到此类选定术语的本地节点。基于真实数据集的实验结果表明，与现有方法相比，所提出的解决方案是有效的。尤其是，显示了基于相似度的过滤器复制可以减轻由于某些文档术语比其他文档术语更为普遍而引起的热点的影响。

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