Abstract

To efficient process of large data set and quick integration in grid computing using the key matching, K-NN and cladogam method, that deals with lot of computing resources and each resource will locate in different locations. Data keep in various localities are searched in parallel mode and firmly accessed and permit to share the info between numerous grids by exploitation searching, key matching techniques. Key matching technique is the process in which two dataset are mapped together by matching the key. The key generated by the algorithm will be used to match the datasets. And Data integration is used to integrate different datasets from various localities into one large dataset. By using key matching algorithm the each dataset can assign different key it helps to integrate different dataset which lies in different location. This helps to integrate single level clusters into multiple clusters. From the general finding of this analysis study conjointly well-tried that our planned frame work might perform higher within the handling of huge knowledge storage and access than different existing frame work utilized in grid computing environments.

Keywords:

Cladogram algorithm, data integration , grid computing , key matching , K-NN,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.