Optimization Algorithm Inspired by Artificial Bee Colonies to Improve Wireless Network Routing

Abstract

Using an AI algorithm, the capacity of wireless multi-channel networks may be increased. It's possible that network performance may increase if interference was reduced. This method has three stages: first, a model of the wireless environment is created; second, performance is optimised using the appropriate tools; and third, routing is improved by carefully picking performance metrics. The communication in wireless networks is improved by the use of an artificial bee colony optimization method with evaluation characteristics. This technique uses the straightforward actions of bee agents to make synchronised and distributed routing choices. The MATLAB simulations clearly show the benefits of this technique. As compared to the current state-of-the- art models, the performance of the routing algorithm inspired by nature is much higher. Even a very basic agent model has the potential to boost the network's performance. When trying to maximise the output of a routing protocol, the breadth-first search version is used to find and deterministically weigh all of the possible pathways across a network.