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Efficient Data Clustering Techniques for Software-Defined Network Centres

Efficient Data Clustering Techniques for Software-Defined Network Centres
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Author(s): Vinothkumar V. (Department of Computer Science and Engineering, Jain University, India), Muthukumaran V. (REVA University, India), Rajalakshmi V. (REVA University, India), Rose Bindu Joseph (Christ Academy Institute for Advanced Studies, India)and Meram Munirathnam (Rajiv Gandhi University of Knowledge Technologies, India)
Copyright: 2022
Pages: 17
Source title: Handbook of Research on Technologies and Systems for E-Collaboration During Global Crises
Source Author(s)/Editor(s): Jingyuan Zhao (University of Toronto, Canada)and V. Vinoth Kumar (Jain University, India)
DOI: 10.4018/978-1-7998-9640-1.ch014

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Abstract

In a smart system, a software-defined network (SDN) is frequently used to monitor and manage the communication organisation. Large-scale data analysis for SDN-based bright networks is gaining popularity. It's a potential technique to deal with a large amount of data created in an SDN-based shrewd lattice using AI advancements. Nonetheless, the disclosure of personal security information must be considered. Client power conduct examination, for example, may result in the disclosure of personal security information due to information bunching. Clustering is an approach for displaying models' observations, data items, or feature vectors in groups. Batching addresses has been catered to in various interesting circumstances and by masters in distinct requests; it gleams far-reaching attractiveness and assistance as one of the ways in exploratory data examination and moreover increases the genuine assessment of data. In this chapter, the authors conduct a study of packing and its various types and examine the computation. Finally, they use it to create an outline model.

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