A Survey and a Layered Taxonomy of Software-Defined Networking

Yosr Jarraya, Taous Madi, Mourad Debbabi

IEEE Communications Surveys & Tutorials · 2014 · 369 citations · 117 references

Concepts

TL;DR

Software‑defined networking has attracted widespread attention, building on programmable networks and control‑data plane separation, and promises simplified management, increased programmability, and reduced CAPEX and OPEX. The paper analyzes and categorizes research works to realize SDN promises. The authors review SDN roots, architecture, existing taxonomies, propose a new layered taxonomy, and compare current research initiatives while highlighting adoption issues. The study identifies foreseeable future research challenges for SDN.

Abstract

Software-defined networking (SDN) has recently gained unprecedented attention from industry and research communities, and it seems unlikely that this will be attenuated in the near future. The ideas brought by SDN, although often described as a "revolutionary paradigm shift" in networking, are not completely new since they have their foundations in programmable networks and control-data plane separation projects. SDN promises simplified network management by enabling network automation, fostering innovation through programmability, and decreasing CAPEX and OPEX by reducing costs and power consumption. In this paper, we aim at analyzing and categorizing a number of relevant research works toward realizing SDN promises. We first provide an overview on SDN roots and then describe the architecture underlying SDN and its main components. Thereafter, we present existing SDN-related taxonomies and propose a taxonomy that classifies the reviewed research works and brings relevant research directions into focus. We dedicate the second part of this paper to studying and comparing the current SDN-related research initiatives and describe the main issues that may arise due to the adoption of SDN. Furthermore, we review several domains where the use of SDN shows promising results. We also summarize some foreseeable future research challenges.

References

117