Artificial intelligence enabled software-defined networking: A comprehensive overview

Name: Artificial intelligence enabled software-defined networking: A comprehensive overview
Author: Latah, Majd, Toker, L.

İsim	Artificial intelligence enabled software-defined networking: A comprehensive overview
Yazar	Latah, Majd, Toker, L.
Basım Tarihi:	2019-03
Basım Yeri	- The Institution of Engineering and Technology
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2047-4954
Kayıt Numarası	c05af33c-20ea-4113-9323-b4eab40659f9
Tarih	2019-03
Örnek Metin	Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.
DOI	10.1049/iet-net.2018.5082
Cilt	8

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Artificial intelligence enabled software-defined networking: A comprehensive overview

Yazar Latah, Majd, Toker, L.

Basım Tarihi 2019-03

Basım Yeri - The Institution of Engineering and Technology

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2047-4954

Kayıt Numarası c05af33c-20ea-4113-9323-b4eab40659f9

Tarih 2019-03

Örnek Metin Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

DOI 10.1049/iet-net.2018.5082

Cilt 8