An Approach for Traffic Prediction in SDN for Performing Routing
Abstract: With the increasing use of smart devices for communications and an increased online mode of operation there is a rapid growth in the rate of traffic flowing through the network. This is driving today?s network operation styles and hence there is a need for technology which can support the service providers in catering to the demands of its users in providing the required service. To be able to perform the above mentioned Software Defined Networks (SDN) has evolved over the years. SDN is an emerging paradigm that supports the network operations to be performed more dynamically and efficiently and hence providing seamless service to the users. In this paper, we propose a Traffic prediction approach. Traffic prediction is performed using Deep learning techniques which helps in performing routing dynamically and cater to the needs of the users.
Keywords: SDN, Software Defined Network, Mean Square Error, MSE, Quality of Service, QoS
How to Cite?: H. Pavithra, Dr. G. N. Srinivasan, "An Approach for Traffic Prediction in SDN for Performing Routing", Volume 11 Issue 6, June 2022, International Journal of Science and Research (IJSR), Pages: 428-429, https://www.ijsr.net/getabstract.php?paperid=SR22604123214, DOI: https://dx.doi.org/10.21275/SR22604123214