Artificial Intelligence Enabled Software Defined Networking: A Comprehensive Overview

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 showed 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, we provide a detailed overview of the recent efforts to include AI in SDN. Our 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 we investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

When deep learning meets security

“…Machine learning techniques have proven to be very useful in networking [1] in general and security related topics in particular [2,3,4]. Deep learning [5][6][7], on the other hand, has improved the state-of-the-art for many machine learning tasks such as speech recognition, objection detection and natural language understanding.…”