Modelling and Performance Evaluation of IoT Network During the COVID-19 Pandemic Abdessamad Bellouch 1(B ) , Ahmed Boujnoui 1 , Abdellah Zaaloul 2 , and Abdelkrim Haqiq 1,3 1 Faculty of Sciences and Techniques, Computer, Networks, Mobility and Modeling Laboratory: IR2M, Hassan First University of Settat, 26000 Settat, Morocco {a.bellouch,a.boujnoui,abdelkrim.haqiq}@uhp.ac.ma 2 F.S.J.E.S. Ait Melloul, Complex System and Interactions Research Team, Ibn Zohr University, Agadir, Morocco a.zaaloul@uiz.ac.ma 3 Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA Abstract. Information from COVID-19 IoT (Internet of Things) devices is greatly important when it is fresh. However, the packets’ col- lision problem slows down the speed at which this information reaches, resulting in a wider spread of the virus. In this paper, we address this challenge by giving priority to COVID-19 IoT devices over consumer IoT devices. We propose a two-dimensional Markov chain for modelling the IoT network including COVID-19 IoT devices, then we derive the per- formance metrics. Our numerical results show a significant improvement in the performance of COVID-19 IoT network in terms of throughput and average delay. Our approach provides a reliable and fast wireless connection of COVID-19 IoT devices to the gateway. Keywords: Markov chain · Internet of Things · Performance evaluation · Wireless networks · COVID-19 1 Introduction and Motivation Internet of Things (IoT) [1] concept is not just restricted to smart homes or smart cities, but they already play a significant role in beating contagious diseases [2], including the COVID-19 pandemic [3–5]. COVID-19 outbreak can be a decisive occasion that further widens the digital split between those who despise digital initiatives and those that support them [6]. For example, during the COVID- 19 pandemic, many hospitals do not have the capacity to treat all the patients as all doctors have been mobilized to treat COVID-19 patients [7]. However, IoT technology provides a possibility to help healthcare professionals remote access accurate and personalized data about their patients, improve the speed and accuracy of diagnosis and treatments, and monitor their health status in real-time [8–10]. The technology can be also used for pandemic surveillance and c  The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 A. Abraham et al. (Eds.): IBICA 2020, AISC 1372, pp. 131–140, 2021. https://doi.org/10.1007/978-3-030-73603-3_12