Overlapped Text Partition Algorithm for Pattern Matching on Hypercube Networked Model

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Assoc. Prof. Ksmvkumar
Assoc. Prof. Ksmvkumar
σ
Prof. S. Viswanadha Raju
Prof. S. Viswanadha Raju
ρ
Prof. A .Govardhan
Prof. A .Govardhan
α Jawaharlal Nehru Technological University, Hyderabad

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Overlapped Text Partition Algorithm for Pattern Matching on Hypercube Networked Model

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Abstract

The web has been continuously growing and getting hourglass shape. The indexed web is measured to contain at least 30 billion pages. It is no surprise that searching data poses serious challenges in terms of quality and speed. Another important subtask of the pattern discovery process is sting matching, where in which the pattern occurrence is already known and we need determine how often and where it is occurs in given text. The target of current research challenges and identified the new trends i.e distributed environment where in which the given text file is divided into subparts and distributed to N no. of processors organized in hypercube networked fashion .To improve the search speed and reduce the time complexity we need to run the string matching algorithms in parallel distributed environment called as hypercube networked model using RMI method. we considered both KV-KMP and KV-boyer-moore string matching algorithms for pattern matching in large text data bases using three data sets and graph’s drawn for different patterns.

References

16 Cites in Article
  1. (1977). KV-BM algorithms results on line graph for Matching in Strings.
  2. R Boyer,J Moore (1977). A fast String Searching Algorithm Communications of the ACM.
  3. Abdulrahman Awsan,Nurainiabdul Hasan,Rashid (2012). Hash-Boyer Moore-Harspool string Matching Algorithm for Intrusion Detection Systems.
  4. Alfred Aho,Margaret Corasick (1975). Efficient string matching.
  5. B Allen,Wilkinson (1999). Parallel Programming: Techniques and Applications using Networked Workstations and Parallel Computers.
  6. S Viswanadha Raju,A Vinaya,Babu (2006). Optimal Parallel Algorithm for String Matching on Mesh Network Structure.
  7. S Viswanadha Raju,S Mantena,A Vinayababu,Raju (2006). Efficient Parallel String Matching Using Partition Method.
  8. (2008). Delano-Osborne, Major-General Osborne Herbert, (1879–12 Nov. 1958), Royal Scots Fusiliers.
  9. Bi Kun,Gu Nai-Jie,Tu Kun,Liu Xiao-Hu,Liu Gang (2005). A Practical Distributed String matching Algorithm Architecture and Implementation.
  10. Zvi Galil (1995). A Constant-Time Optimal Parallel String-Matching Algorithm.
  11. Hiroki Arimura,Atsushi Wataki,Ryoichi Fujino,Setsuo Arikawa (1998). A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases.
  12. Jin Hwan,Park,K George Parallel String Matching Algorithms Basedon Dataflow.
  13. Rivest Cooks (1977). Two-way pushdown automata for string matching.
  14. Y Mishina,K Kojima (1993). String matching on IDP: a string matching algorithm for vector processors and its implementation.
  15. R Sidhu's,V Prasarna (2001). Fast regular Expression Matching using FPGA's.
  16. Edward Fernandez,Walid Najjar,Stefano Lonardi (1998). String Matching in Hardware Using the FM-Index.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Assoc. Prof. Ksmvkumar. 2013. \u201cOverlapped Text Partition Algorithm for Pattern Matching on Hypercube Networked Model\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 13 (GJCST Volume 13 Issue E4): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Version of record

v1.2

Issue date

April 18, 2013

Language
en
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The web has been continuously growing and getting hourglass shape. The indexed web is measured to contain at least 30 billion pages. It is no surprise that searching data poses serious challenges in terms of quality and speed. Another important subtask of the pattern discovery process is sting matching, where in which the pattern occurrence is already known and we need determine how often and where it is occurs in given text. The target of current research challenges and identified the new trends i.e distributed environment where in which the given text file is divided into subparts and distributed to N no. of processors organized in hypercube networked fashion .To improve the search speed and reduce the time complexity we need to run the string matching algorithms in parallel distributed environment called as hypercube networked model using RMI method. we considered both KV-KMP and KV-boyer-moore string matching algorithms for pattern matching in large text data bases using three data sets and graph’s drawn for different patterns.

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Overlapped Text Partition Algorithm for Pattern Matching on Hypercube Networked Model

Assoc. Prof. Ksmvkumar
Assoc. Prof. Ksmvkumar Jawaharlal Nehru Technological University, Hyderabad
Prof. S. Viswanadha Raju
Prof. S. Viswanadha Raju
Prof. A .Govardhan
Prof. A .Govardhan

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