IoT Node Selection and Placement: A New Approach Based on Fuzzy Logic and Genetic Algorithm

Abstract

The enormous growth of devices having access to the Internet, along the vast evolution of the Internet and the connectivity of objects and devices, has evolved as Internet of Things (IoT). There are different issues for these networks. One of them is the selection and placement of IoT nodes. In this work, we propose a simulating system based on Fuzzy Logic and Genetic Algorithm for IoT node selection and placement. We consider three input parameters for our Fuzzy-based selection system: IoT Node Density (IND), IoT Node’s Remaining Energy (INRE) and IoT Node’s Distance to Event (INDE). We also present a simulation system based on Genetic Algorithm which is implemented in Rust, for IoT node placement. We consider different aspects of an IoT network, considering coordination, connectivity and coverage. We describe the implementation and show the interface of simulation system. We evaluated the performance of the proposed system by a simulation scenario. For the IoT node fuzzy-based selection system, we show that the system makes a proper selection of IoT nodes. The simulation results of GA-based system show that the constructed network, can cover both events.