Optimization of Network paths in congested SDN using Genetic Algorithm

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Computer network and Communication over such networks become integral part of human life from the very beginning of twenty first century. From the very first radio communication in the beginning of 19th Century to the latest wireless and Software Defined Network (SDN) communication over the satellite and local allied computer networks, caused increase in more and more traffic over the computer network. Internet was not only provided over the copper, fiber optics cables, but rather it becomes a commercial service sector over the low earth orbit satellites across the globe. Majority of the contents flowing over such networks are either academic, research, corporate data bases like banking, finance, IT services, social media, and also specially of the entertainment industry. Every small to large organization in corporate and research and development organization faced problems of computer network congestion over the time. As the demand for more data access is required hence the congestion over the network started to increase. Every nation and individual organization have their own policy to control domestic network traffic as bandwidth is limited and commercial aspects are involved. Various algorithms have focused to regulate network, but very few algorithms exist which focuses on providing alternative paths for better network traffic management. This paper focuses on using modern Genetic Algorithms like Ants colony optimization to first identify congestions over the network and then using such insights to find alternative paths through mutation and cross over. The proposed solution was executed, and generated result comparatively proved that use of Genetic Algorithm has helped to find alternative paths more effectively over the SDN.