An Approximate Top-k Query Algorithm in Distributed Networks

Wenhua Li, Wenting Yu, Xiaon'an Feng
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Abstract

In this paper, we propose a variant algorithm Rough Classification based on the Precutting parameter p (RCP). As the distribution of page requests generally follows a Zipf-like distribution, RCP precuts the object by predicting the derived bounds and so that to drop candidate items. By pretreatment, RCP can reduce bandwidth consumption and the run-time cost with high precision in some cases. Furthermore, by performance evaluations using both theoretical analysis and computer simulations, we show that the proposed algorithm can reduce the bandwidth consumption.
分布式网络中的近似Top-k查询算法
本文提出了一种基于预切参数p (RCP)的粗糙分类算法。由于页面请求的分布通常遵循类似zipf的分布,因此RCP通过预测派生边界来预切对象,从而删除候选项。通过预处理,RCP可以在某些情况下以较高的精度降低带宽消耗和运行时间成本。此外,通过理论分析和计算机模拟的性能评估,我们表明所提出的算法可以减少带宽消耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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