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Big Data and Software Defined Networks

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IET Digital Library

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  • Book title: Big Data and Software Defined Networks

  • Author:

  • Year: 2018

  • Format: Hardback

  • Product Code: PBPC0150

  • ISBN: 978-1-78561-304-3

  • Pagination: 504pp

  • Stock Status: In stock

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Description

Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data and usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). SDN helps CDCs run their services more efficiently by enabling managers to configure, manage, secure, and optimize the network resources very quickly. Big-Data Analytics in turn has entered CDCs to harvest the massive computing powers and deduct information that was never reachable by conventional methods. Big Data and Software Defined Networks investigates areas where Big-Data and SDN can help each other in delivering more efficient services. SDN can help Big-Data applications overcome one of their major challenges: message passing among cooperative nodes. Through proper bandwidth allocation and prioritization, critical surges of Big-Data flows can be better handled to effectively reduce their impacts on CDCs. Big-Data, in turn, can help SDN controllers better analyze collected network information and make more efficient decisions about the allocation of resources to different network flows.

Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). SDN helps CDCs run their services more efficiently by enabling managers to configure, manage, secure, and optimise the network resources very quickly. Big-Data Analytics in turn has entered CDCs to harvest the massive computing powers and deduct information that was never reachable by conventional methods. In this new edited reference the authors investigate areas where Big-Data and SDN can help each other in delivering more efficient services.

About the Editor

Javid Taheri is an Associate Professor at the Department of Computer Science, Karlstad University, Sweden where his research interests include networking, optimisation, parallel/distributed computing, and cloud computing. He holds a PhD in Information Technologies, 2007. From the School of Information Technologies, The University of Sydney, Australia.

Book readership

This book is ideal for engineers, scientists, researchers, developers and practitioners developing and/or implementing cloud-based solutions. Also suitable for academics working in networking and SDN, machine learning, Big-Data analytics and optimisation disciplines; and cloud infrastructure designers and cloud providers hosting Big-Data services.

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