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An Optimal Algorithm for Matching String Patterns in Large Text Databases

机译:大型文本数据库中匹配字符串模式的最佳算法

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Modern parallel distributed string matching algorithms are always based on networked computation model. Those algorithms depends on the cost optimal design and the theoretical speed. The motive of current research challenges and identified the new directions I.e distributed environment where in which the given text file is divided into subparts and distributed to PI to PN no. of processors organized in parallel environment called as hypercube network. Based on the distributed memory machine string matching algorithms proposed by CHEN and BI-Kun, a optimal algorithm for matching string patterns in large text databases over parallel distributed hypercube networked architecture is proposed in this paper. And also an improved parallel string matching algorithm based on a variant Boyer-Moore algorithm is presented. We implement our hype and integrated algorithms on the above architecture and the experiments are proven that it is truly practical and efficient on parallel distributed Hypercube networked model. Its computation complexity is O(T/p + m-1), where T is text file of length n characters, and m is the length of the pattern, and p is the number of the processors.
机译:现代并行分布式字符串匹配算法始终基于网络计算模型。这些算法取决于成本优化设计和理论速度。当前研究挑战的动机并确定了新的方向,即分布式环境,在该环境中,给定的文本文件分为多个子部分,并分发给PI至PN号。在称为“超立方体网络”的并行环境中组织的处理器数量。基于CHEN和BI-Kun提出的分布式存储机字符串匹配算法,提出了一种在并行分布式超立方体网络体系结构上匹配大型文本数据库字符串模式的优化算法。并提出了一种基于变式Boyer-Moore算法的并行字符串匹配算法。我们在上述架构上实现了炒作和集成算法,并且实验证明,它在并行分布式Hypercube网络模型上是真正实用和高效的。它的计算复杂度为O(T / p + m-1),其中T是长度为n个字符的文本文件,m是模式的长度,p是处理器的数量。

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