Planning and Optimization of Software-Defined and Virtualized IoT Gateway Deployment for Smart Campuses

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-06, Vol.22 (13), p.4710
• Main Authors: Ferreira, Divino, Oliveira, João Lucas, Santos , Carlos, Filho, Tércio, Ribeiro, Maria, Freitas, Leandro Alexandre, Moreira, Waldir, Oliveira-Jr, Antonio
• Format: Article
• Language: English
• Subjects: Algorithms; cluster; Clustering; College campuses; Communication; Costs; Data links; Geographical distribution; Heterogeneity; Hypothesis testing; Internet of Things; Internet of Things (IoT); IoT gateway; Linear programming; Methods; Optimization; Optimization models; smart campus; Smart cities; Software; Technology; Wireless access points; Wireless communications; Wireless networks
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22134710

The Internet of Things (IoT) is based on objects or “things” that have the ability to communicate and transfer data. Due to the large number of connected objects and devices, there has been a rapid growth in the amount of data that are transferred over the Internet. To support this increase, the heterogeneity of devices and their geographical distributions, there is a need for IoT gateways that can cope with this demand. The SOFTWAY4IoT project, which was funded by the National Education and Research Network (RNP), has developed a software-defined and virtualized IoT gateway that supports multiple wireless communication technologies and fog/cloud environment integration. In this work, we propose a planning method that uses optimization models for the deployment of IoT gateways in smart campuses. The presented models aimed to quantify the minimum number of IoT gateways that is necessary to cover the desired area and their positions and to distribute IoT devices to the respective gateways. For this purpose, the communication technology range and the data link consumption were defined as the parameters for the optimization models. Three models are presented, which use LoRa, Wi-Fi, and BLE communication technologies. The gateway deployment problem was solved in two steps: first, the gateways were quantified using a linear programming model; second, the gateway positions and the distribution of IoT devices were calculated using the classical K-means clustering algorithm and the metaheuristic particle swarm optimization. Case studies and experiments were conducted at the Samambaia Campus of the Federal University of Goiás as an example. Finally, an analysis of the three models was performed, using metrics such as the silhouette coefficient. Non-parametric hypothesis tests were also applied to the performed experiments to verify that the proposed models did not produce results using the same population.