Probabilistic Position Estimation and Model Checking for Resource-Constrained IoT Devices

Abstract

The Internet of Things (IoT) has been applied to home/office, healthcare, intelligent transportation and agriculture systems. The new IoT technology are growing rapidly and will play an essential role in our future societal lifestyle, economy and business. Currently, power hungry and radio wave interference are two big challenges hindering the IoT development. In this study, we propose a Markov localization algorithm to estimate positions of IoT devices considering various gateway allocation scenarios in a widespread and boundaryless field. We adopt the model-checking technique to validate the convergence of positions of the IoT devices. Our approach can accurately identify positions of IoT devices and connect each IoT node to its nearest gateways for sending sensing data and receiving commands from the cloud computing resources. We use a cattle-breeding IoT network as a case study to validate the proposed approach,which reduces IoT power consumption while enhancing the connectivity of the network. Additionally, we also discuss how to apply this simple approach to real-world IoT networks such as smart home and vehicular ad-hoc networks.