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SDN helps volume in Big Data
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO)ORCID-id: 0000-0001-9866-8209
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO)ORCID-id: 0000-0001-7734-1653
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO)ORCID-id: 0000-0001-9194-010X
2018 (engelsk)Inngår i: Big Data and Software Defined Networks / [ed] Javid Taheri, London: IET Digital Library, 2018, 1, s. 185-206Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Both Big Data and SDN are described in detail in previous chapters. This chapter investigates how SDN architecture can leverage its unique features to mitigate the challenges of Big Data volume. Accordingly, first, we provide an overview of Big Data volume, its effects on the underlying network, and mention some potential SDN solutions to address the corresponding challenges. Second, we elaborate more on the network-monitoring, traffic-engineering, and fault-tolerant mechanisms which we believe they may help to address the challenges of Big Data volume. Finally, this chapter is concluded with some open issues.

sted, utgiver, år, opplag, sider
London: IET Digital Library, 2018, 1. s. 185-206
Emneord [en]
Big Data; software fault tolerance; software defined networking; telecommunication traffic
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-67212DOI: 10.1049/PBPC015E_ch9ISBN: 978-1-78561-304-3 (tryckt)ISBN: 978-1-78561-305-0 (digital)OAI: oai:DiVA.org:kau-67212DiVA, id: diva2:1202068
Tilgjengelig fra: 2018-04-27 Laget: 2018-04-27 Sist oppdatert: 2019-11-07bibliografisk kontrollert

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Forlagets fullteksthttp://digital-library.theiet.org/content/books/10.1049/pbpc015e_ch9;jsessionid=4af710hogc0kq.x-iet-live-01

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Alizadeh Noghani, KyoomarsHernandez Benet, CristianTaheri, Javid

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