Optimization Flow Control In Software-Defined Networking Using Cuckoo Search Algorithm

Abstract

Network managers can scale their networks more easily and experience fewer issues by using software-defined networking. They have evolving requirements over time, just like big scale networks like data centers. The speed at which data is transferred between nodes and the expense of the physical equipment are both very important. This thesis offers a framework for avoiding network momentum by using the cuckoo search algorithm to find the best path at the lowest cost, as well as for lowering the cost of the network's physical equipment when it needs to be expanded and for lowering the time it takes to send packets after finding the shortest path as the network is built in different sizes. It is generated automatically using the Spanning Tree Protocol. (STP), where the virtual ring-free network is built using data connection layer of the OSI model system, and the paths are then computed using the paths calculation algorithm and the cost of each route. The fitness function, one of the steps in utilizing the cuckoo search method is used to ascertain the best path, which primarily relies on time and distance factors.