A Review on Application of Machine Leaning for Routing in Optical Multistage Interconnection Networks

Artificial neural networks is also known as machine learning or deep learning which  have been studied for many years in order of achieving human performance like in the fields of speech and image recognition. These networks are made up of many nonlinear computational elements operating in same and arranged in patterns which reminds the biological neural nets. This paper presents a case study about the use of neural network computational algorithms for optical networks. These algorithms are determined the use of optimal traffic routing for communication networks. Neural network solution is used in case of Optical Multistage Interconnection Networks (OMINs) in order to avoid crosstalk. The routing technique makes use of an machine learning that function as a parallel computer for generating the routes. It concludes that neural network gives better outcomes in terms of speed and crosstalk avoidance.