ADVANCED ALGORITHMS FOR SDN TRAFFIC CLASSIFICATION TO OPTIMIZE QUALITY OF SERVICE

Abstract

The paradigm shift known as Software Defined Networking (SDN) allows for more dynamic and programmable network administration by separating the control plane from the data plane. Network performance needs to be dependable and predictable, and thus requires Quality of Service (QoS). Identifying SDN traffic for QoS control has become essential for network resource optimization. Routing protocols and set configurations are common features of traditional network management systems. Although they work well in many situations, they might not be able to deliver granular QoS in response to changing traffic conditions due to their lack of adaptation and flexibility. Creating a classification system that correctly distinguishes between various types of traffic in an SDN environment is the main problem. In order to do this, algorithms that can evaluate network packets and classify them according to their attributes and quality of service criteria must be developed. Classifying traffic is therefore essential for dynamic and complicated networks in order to guarantee that various data kinds receive the proper degree of service. Prioritizing real-time communication, making sure there is enough bandwidth for essential apps, and effectively managing resources are all part of this. The inability of traditional networks to adjust to shifting traffic patterns emphasizes the need of SDN and QoS. The goal of the project, "Classification of Software Defined Network Traffic to Provide Quality of Service," is to use SDN's QoS optimization capabilities to transform network management. This project aims to build sophisticated algorithms for traffic categorization so that a system that can accurately and independently classify network traffic in real-time may be created. This categorization enables the use of certain QoS criteria made for various kinds of traffic, guaranteeing the best possible network performance and resource distribution. This development has enormous potential to improve network operations' efficacy and efficiency, especially in settings with varied and dynamic traffic patterns.