Enhancement of Map Function Image Processing System using DHRF Algorithm on Big Data in the Private Cloud Tool

Abstract

Cloud computing is the concept of distributing a work and also processing the same work over the internet. Cloud computing is called as service on demand. It is always available on the internet in Pay and Use mode. Processing of the Big Data takes more time to compute MRI and DICOM data. The processing of hard tasks like this can be solved by using the concept of MapReduce. MapReduce function is a concept of Map and Reduce functions. Map is the process of splitting or dividing data. Reduce function is the process of integrating the output of the Map’s input to produce the result. The Map function does two various image processing techniques to process the input data. Java Advanced Imaging (JAI) is introduced in the map function in this proposed work. The processed intermediate data of the Map function is sent to the Reduce function for the further process. The Dynamic Handover Reduce Function (DHRF) algorithm is introduced in the reduce function in this work. This algorithm is implemented in the Reduce function to reduce the waiting time while processing the intermediate data. The DHRF algorithm gives the final output by processing the Reduce function. The enhanced MapReduce concept and proposed optimized algorithm is made to work on Euca2ool (a Cloud tool) to produce an effective and better output when compared with the previous work in the field of Cloud Computing and Big Data.

The Dialectics of Science and Magnetism

March 16, 2026

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GJCST Volume 14 Issue B2

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