Abstract
Logically programmed cluster provides the platform to compute certain complex problems which are not solvable on a single system. Parallel processing implemented on a distributed data, on a cluster with the help of multithreading is a base for the present work. It is very easy for an application based on parallelism to beat the results produced by the sequential program on the same platform. Taking this thing into consideration along with the cluster programming can be used to solve certain complex problems like processing of large size images to apply median filtering. In the present work, an image with large dimensions is break down into sub images with lesser dimensions and this breakdown is as per the number of nodes under consideration from a given cluster. For the purpose of communication between these nodes distributed object oriented programming remote method invocation (RMI) is used which creates a Single Instruction and Multiple Data (SIMD) model. At the master system there is actual breakdown of the image into smaller dimensions and at the slave systems there is virtual division of the sub image further into 3 × 3 or as per mask selected to apply median filter. Various performance metrics like Excessive parallel overhead (EPO), Overall Computation Time (OCT), Speed Up (SU) and Efficiency are calculated to find out the effectiveness of the proposed cluster.
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Bagga, S., Girdhar, A., Trivedi, M.C., Bao, Y., Du, J. (2018). RMI Approach to Cluster Based Image Decomposition for Filtering Techniques. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-10-3773-3_38
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DOI: https://doi.org/10.1007/978-981-10-3773-3_38
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