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Scientific workflow management system for community model in data fusion
Published in Springer Verlag
Volume: 458
Pages: 363 - 370
The scientific experiments handle huge amount of data from various sources. The processing of data includes various computing stages along with their dependency pattern. The scientific workflow for data-intensiveness is used to model different processes. The scientific workflow paradigm integrates, structures and orchestrates services of heterogeneity and software design tools locally and globally to form scientific processes with complexity for enabling scientific discoveries. The Scientific Workflow Management System (SWfMS) deploys the scientific workflows for data-intensiveness by means of executing parallelism and the resources distributed in different infrastructures like grid and cloud. The community model is a data fusion methodology which is used to fuse data from various sources with multiplicity. The SWfMS for community model is used to describe the flow of data in various parts of the model and their corresponding working principle. This paper presents a data-intensive SWfMS for the community model. © Springer Science+Business Media Singapore 2017.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag
Open AccessNo