# Modeling and Fault Tolerance Analysis of ZigBee Protocol in IoT Networks
## 1 Introduction  
Today's technologies are developing very fast and hence many of the newly developed solutions minimize or even exclude human intervention, especially in IoT infrastructures. Devices do not require initial configuration or time-consuming setup, and the user only needs to start them up, which is almost immediately ready for operation. Such solutions include the Internet of Things, which has been intensively developed since the late 1990s. The balance between network lifetime optimization and load distribution among sensor nodes is crucial for the development of energy-efficient routing solutions. The purpose of the simulations and analysis presented here is to model the operation and fault tolerance capabilities of an IoT network based on one of the most popular communication protocols, which is the ZigBee protocol. The ZigBee network topology was created and different configurations were implemented in which various node failure scenarios were simulated to show its robustness to node and adjacent links failures. The problem of ensuring continuous and secure operation is a challenge in the age of cyber threats, constantly evolving new services and hardware. Dozens, hundreds, or even thousands of devices within a single IoT infrastructure are constantly vulnerable to attack. Today, IoT solutions are used in many areas of life, including those relevant to protecting human health and life. This paper addresses the topic of modeling and fault tolerance analysis of selected IoT network protocol, in order to evaluate the protocol for different failure scenarios assuming the failure of various IoT network nodes. In wireless sensor networks (WSNs), resource constraints are a key factor influencing the choice of a routing protocol as well as the design of the network management application. The routing algorithm used in WSN has a direct impact on the energy consumption of the sensors. Failure to match the routing algorithm will increase the packet traffic, not only limiting the network performance but more importantly will increase the energy consumption ofthe nodes, which will then translate into a reduction in their operating time, consequently shutting them down. Many academics have tried to emphasize different aspects of the IoT, such as security, communication, or providing energy and reducing energy consumption. Using traditional programming methods to effectively coordinate devices can be inefficient. This is due to a large number of nodes and their connections. In [1], the authors present a framework for collective programming based on field calculus and APIs based on building blocks. In field calculus, each expression, variable, or value is represented as a field, for example, a collection of temperature sensors forms an ambient temperature field. Using such a solution significantly simplifies the programming and device coordination process. By analyzing the work of [2], we can in turn identify a method to provide a stable, open, and evolving infrastructure that can form the basis for IoT development. The authors built a test environment in which they implemented several important features such as service discovery, human interactivity user location, and security. The authors of the paper [3] present a new approach to using web analytics to advance the Internet of Things. They describe in detail a cloud-based mapping service that can interpret IoT events into matching web analytics events. The authors also provide concrete examples showing how to use the service. Cloud computing can be widely used in IoT providing support for computation, a place to store collected data, and also as middleware to integrate multiple devices.