Modeling and simulation of Internet of Things networks in smart buildings using queuing theory
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Abstract
Smart building systems in major cities are equipped with Internet of Things devices to monitor some different indicators in these buildings, and for the purpose of avoiding a decrease in the quality of service for these systems. Therefore, performance indicators related to their performance must be determined before implementing the building. Through these indicators, the behavior of the system can be understood and analyzed to estimate its performance quantitatively. In this study, the queue network model was used to model and simulate a smart building consisting of two floors and five rooms, where the main room is equipped with sensors. The modeling of the smart building system included three different levels: the edge computing level, the fog computing level, and the cloud computing level. The building was simulated using the Java Modeling Tool program, which allows simulating the queue model, and through it the performance indicators for the scenario of changing the number of servers can be estimated and the scenario parameters determined. Based on previous studies, the following indicators were adopted to study the behavior of the system, which are: average response time (R), number System messages (N), utilization ratio (U), flow rate (
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