Insight Thoughts for Intelligent Traffic Management-Based SDN
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Abstract
The trend towards studying traffic management in software-defined networks (SDN) is increasing widely due to its great importance in enhancing the efficiency of networks and their abilities to adapt to the increasing demands on data and modern applications. What increases the importance of these studies is the integration of artificial intelligence (AI) technologies, which in turn provide intelligent analysis and response capabilities that contribute to improving quality of service (QoS), avoiding congestion, and achieving balanced load distribution across the network. Intelligent management in the SDN controller involves the use of modern algorithms and technologies that have been used previously and have given desirable results in this field to improve the control, configuration and automation of network resources in an advanced manner. As for SDN controllers, they have a key role in SDN architectures, as they are responsible for managing the flow of data to network devices in the Data Plane layer such as Switches and Routers. This paper introduces the integration of AI algorithms into the SDN controller so that you can make intelligent decisions using predictive analytics of future traffic, what it requires, and network capacity requirements. In addition to presenting a valuable comparison in this paper, which includes the approach of others followed in smart traffic management for SDN networks. The process of integrating artificial intelligence and SDN opens up prospects towards developing advanced networks that support the requirements of modern networks, such as the Internet of Things, communications, and others. The main focus is on comprehensive integration so that research is an effective contribution and keeps pace with the continuous development of smart grid management strategies.
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