The Emerging Role of Integrating Artificial Intelligence (Ai) in the Software Defined Network for Effective Traffic Prediction using Correlation Analysis

Traffic technology can be improved using SDN as it enhances overall performance, SDN provides flow control capabilities, distributed access restrictions, traffic analysis and conditions and more. SDN offers many benefits over the past. Cultural network design, which provides better planning and control from a global network perspective, is also important for analyzing network status and performance requirements. The next thing is that SDN provides better flexibility as data quality is significantly improved, in order to increase the efficient allocation of network resources…. Flow control provides the ability to address issues related to transportation costs and data quality, but tolerance limits refers to the ability to detect the cause of network failures and respond quickly, and traffic analysis plays an important role in identifying network failures. The TE supports in monitoring the network parameters including the utilisation of the bandwidth, however the critical element is to generate the data related to the utilisation, this also enable in monitoring and traffic analysis in an effective manner. It also warns of congestion or problems in the system. There are two main ways that OFF flow meter data can be collected, the first is to collect the associated controls and then distribute the necessary equipment. Nowadays, various technologies and monitoring technologies have been used to understand the overall performance of the device. The application of AI techniques tends to offer better tacking the aggregation issue and provide better and flexible approach which can be used to manage the network traffic in an effective manner.