An intelligent algorithm for data conversion in distributed computing environment using parallel processing.

Data conversion is one of the major task in computerization and the data mining process. Thousands of private and the governmental organizations are trying to convert the entire paper document to soft documents. In another example many old format wave files need to be keep safe in very low space and there are thousands of historical wave file need to be convert in to lower size file format. Considering such conditions there is a need to employee the system which will transfer processing over the network system and save output on the server or main system, we are proposing a parallel computing model for the distributed computing platforms. This model ensures easy distribution of the software components, files and resources along the participating computers. We are using a concept in the model which creates slave objects dynamically to fulfill the master/slave parallel computing pattern. When compared with the other similar models results show that our model is not only a feasible model for distributed environment but also an efficient approach of data conversion in distributed parallel computing environment.