The Performance Analysis of Traffic Control for load balancing in Software-Defined Wireless Networks

  • K. Rangaswamy, C. Rajabhushanam


The consistent development of the Internet, smart applications, online business, media applications, social networks poses a ceaseless challenge for networks on keeping up with evolution in terms of bandwidth, data overload, and complexity, etc. Enterprises, for example, Google, Facebook, Microsoft, eBay, and Amazon utilize countless server farms. A gigantic volume of information is traded in those centers. Data centers incorporate virtual machines (VMs) to separate the network, coherently the system into various hubs, clusters, or slices. Software Defined Networking (SDN) is an advanced system architecture that spotlights on the partition of control and data planes. In contrast to customary switches, SDN switches incorporate flow tables that are remotely constrained by a different programming application, the controller. SDN isn't totally new; it figures an architecture on top of several good practices. It gives a worldwide perspective on the basic system, making ready for gigantic research in the zone of SDN traffic Engineering (SDN TE). This research focuses on the load balancing aspects of SDN TE, given that the existing reactive methods for data-plane load balancing eventually result in packet loss and proactive schemes for data plane load balancing do not address congestion propagation.  For load adjusting the recognized biggest stream and further traffic through this bottleneck, links are rerouted through the gently lightly loaded alternate path. The simulation results show that when the system traffic builds the proposed technique productively re-courses the streams and equalization the system load which significantly improves the system proficiency and the Quality of Service parameters

How to Cite
C. Rajabhushanam, K. R. (2020). The Performance Analysis of Traffic Control for load balancing in Software-Defined Wireless Networks. International Journal of Control and Automation, 12(6), 697 - 704. Retrieved from