Open Access

ARTICLE

Artificial Intelligence Based Smart Routing in Software Defined Networks

C. Aswini^1,*, M. L. Valarmathi²

1 Department of Information Technology, Government College of Technology, Coimbatore, 641013, India
2 Department of Computer Science and Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, 642003, India

* Corresponding Author: C. Aswini. Email:

Computer Systems Science and Engineering 2023, 44(2), 1279-1293. https://doi.org/10.32604/csse.2023.022023

Received 25 July 2021; Accepted 25 November 2021; Issue published 15 June 2022

Abstract

In a non-static information exchange network, routing is an overly complex task to perform, which has to satisfy all the needs of the network. Software Defined Network (SDN) is the latest and widely used technology in the future communication networks, which would provide smart routing that is visible universally. The various features of routing are supported by the information centric network, which minimizes the congestion in the dataflow in a network and provides the content awareness through its mined mastery. Due to the advantages of the information centric network, the concepts of the information-centric network has been used in the paper to enable an optimal routing in the software-defined networks. Although there are many advantages in the information-centric network, there are some disadvantages due to the non-static communication properties, which affects the routing in SDN. In this regard, artificial intelligence methodology has been used in the proposed approach to solve these difficulties. A detailed analysis has been conducted to map the content awareness with deep learning and deep reinforcement learning with routing. The novel aligned internet investigation technique has been proposed to process the deep reinforcement learning. The performance evaluation of the proposed systems has been conducted among various existing approaches and results in optimal load balancing, usage of the bandwidth, and maximization in the throughput of the network.

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Keywords

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