Improvement of Software-Defined Network Performance Using Queueing Theory: A Survey

Software-Defined Networking (SDN) is a growing network technology that has brought significant benefits to a wide range of disciplines, from science to technology to various fields. This structure can be used in network-based environments, data centers and various research sites. OpenFlow is one of the most widely used protocols for interaction between a controller and a switch in a Software-Defined Networking. Understanding the performance and limitations of the network defined by open source software, including bottlenecks and security vulnerabilities due to the centralized network structure, are important prerequisites for the efficient deployment of these systems. These points of view led researchers to examine various related mathematical models to address these issues. Queueing theory provides the most important and accurate model for evaluating the performance of the SDN networks affected by these restrictions, which has attracted the attention of researchers recently. Regarding to extensive mathematical modeling, this theory has also been used to improve network efficiency. Researchers have used this theory to investigate operational power and improve time consumption and control of data planes due to the nature of classification and storage of packets in SDN buffers. These methods overcome controller performance bottlenecks and increase SDN control capacity, especially for large distributed networks. In this paper, we examine the queueing models for different applications in different layers of SDN, in which researchers use these methods to monitor network loads, evaluate and predict performance changes due to diversity in network traffic. We introduce and review a collection of articles that explore, different applications of Queueing theory in SDN networks. In addition, in order to increase the efficiency of this research, detailed comparisons are performed in terms of structure, mathematical models and the final simulation results.

Keywords:

Queueing Theory , OpenFlow , Performance Enhancement