Overlapped Text Partition Algorithm for Pattern Matching on Hypercube Networked Model
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.
