Minimum UAV Fog Servers with Maximum IoT Devices Association Using Genetic Algorithms

Abstract

Internet of Things (IoT) has emerged as a new technology to enhance many services and applications including the industrial sector; thus, enabling the Industry 4.0 among many others. IoT created many challenges as the services response time requirements have grown more strict and urged the need for faster means of communications and computation processing. To solve this problem, fog computing has emerged to serve IoT devices at closer distances than cloud computing. In this paper, we leverage the Unmanned Aerial Vehicles (UAVs) mounted cloudlets to provide computation offloading opportunities to IoT devices while meeting the latency constraints. We aim at deploying the minimum number of UAVs to serve the maximum number of IoT devices within their deadlines subject to communication and computation constraints. We first formulate the problem as a multi-objective optimization problem which can be shown to be mixed-integer non-linear program (MINLP) and is NP-hard. We then propose a heuristic sub-optimal approach based on genetic algorithm (GA) to decide on the minimum number of UAVs to be deployed and the IoT-to-UAV association. Simulation results demonstrated the efficiency of the proposed approach under different system parameters and constraints in minimizing the number of UAVs while maximizing the number of served IoT devices.