Artificial intelligence enabled software‐defined networking: a comprehensive overview. Issue 2 (1st March 2019)

• Record Type: Journal Article
• Authors: Latah, Majd; Toker, Levent
• Is Part Of: IET networks. Volume 8:Issue 2(2019)
• Page Start: 79
• Page End: 99
• Publication Date: 2019-03-01
• Subjects: learning (artificial intelligence) -- decision making -- fuzzy reasoning -- computer network management -- software defined networking; networking architecture -- SDN paradigm -- AI -- artificial intelligence field -- central point -- network management -- data plane -- control plane -- central management -- comprehensive overview -- software‐defined networking; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2018.5082
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : 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.