Software Defined Networking Flow Table Management of OpenFlow Switches Performance and Security Challenges: A Survey

TLDR

Software‑defined networking decouples control and data planes, is increasingly adopted for its centralized, flexible, programmable management, yet the surge of IoT traffic strains controller processing and flow‑table capacity, causing performance instability and prompting numerous flow‑table management solutions. This survey compiles existing schemes to enable SDN to meet the QoS demands of diverse applications and cloud services. The paper also discusses future research directions, notably applying machine learning to flow‑table management.

Abstract

Software defined networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane. The data plane is composed of forwarding elements called switches and the control plane is composed of controllers. SDN is gaining popularity from industry and academics due to its advantages such as centralized, flexible, and programmable network management. The increasing number of traffics due to the proliferation of the Internet of Thing (IoT) devices may result in two problems: (1) increased processing load of the controller, and (2) insufficient space in the switches’ flow table to accommodate the flow entries. These problems may cause undesired network behavior and unstable network performance, especially in large-scale networks. Many solutions have been proposed to improve the management of the flow table, reducing controller processing load, and mitigating security threats and vulnerabilities on the controllers and switches. This paper provides comprehensive surveys of existing schemes to ensure SDN meets the quality of service (QoS) demands of various applications and cloud services. Finally, potential future research directions are identified and discussed such as management of flow table using machine learning.