Fuzzy logic based on UAV-cloud for service selection

Abstract

The emergence and development of FANET (Flying Ad hoc Network) have contributed to the advancement of technologies in many fields, allowing communication without the need for infrastructure. FANET is an ad hoc network that uses unmanned aerial vehicles (UAVs) to communicate and provide various services. In this case, drones can access a wide range of services like internet access, information, storage, and computing as a service thanks to UAV cloud. But given the high random Because of their mobility, client drones must first identify service providers who can meet their needs before they can use the necessary services. In this project, we propose a new approach called FL_DS, which uses fuzzy logic to solve decision making problems and improve the selection of the best services for UAV clients. This proposed approach is compared with another approach, Simple Additive Weighting (SAW). We utilized the OMNeT++ simulator with the INET framework to create a robust simulation environment. The results demonstrated the effectiveness of fuzzy logic in enhancing network resource management and service quality in FANET