Wireless Networks Throughput Enhancement Using Artificial Intelligence

Objectives: To utilize the correct technique of artificial intelligence in multi-channel network. Multi-channel is used to reduce interference and improve performance. Methods/Statistical Analysis: In this work a simple method has been developed that is a positive contribution to the various solutions that already exists. Overall, the methodology adopted in this work consists of three stages. The first step is to create a model for specific wireless environment, the second step is to choose the right tool to optimize the performance and the third step is the careful selection of performance indicators for routing improvements. Findings: We developed an agent model that is inspired from the communication and evaluative features of a honey bee colony. The bee agents in our model have a simple behavior. As a result, the algorithm is able to take routing decisions in a decentralized and asynchronous fashion. We have conducted extensive simulations in MATLAB to show the advantages of our algorithm over existing state-of-the-art routing algorithms developed by Nature inspired routing community. The candidate algorithm is able to achieve better performance values with a simple agent model. Application/Improvements: The proposed protocol discovers and evaluates multiple-paths in a deterministic fashion by utilizing a variant of breadth first search. It will increase the output of our resulting routing protocol.