# Modeling and Fault Tolerance Analysis of ZigBee Protocol in IoT Networks
## 2 Previous Works  
The Internet of Things (IoT) or the broader term Internet of Everything (IoE) has gained prominence in recent times. The multitude of technological solutions, hardware and software manufacturers means that we are dealing with environments with a high degree of heterogeneity. This aspect can be considered both at the layer of device resources, in terms of memory, processor, and bandwidth, as well as communication resources using bandwidth bands susceptible to errors and loss of quality of radio signals and often deployed in hostile, high interference environment. Moreover, IoT/WSNs experience various network performance issues, e.g., excessive energy consumption due to network device failures and the need to reconfigure the existing structure at the logical layer using energy-expensive routing or self-reconfiguration algorithms. These issues are highlighted by the authors of the paper [12], stating that, in this context, effective management of IoT/WSNs is needed to ensure good network performance. This drives the development of various protocols and frameworks for managing IoT/WSN networks. A major challenge for network designers is scalability. This process generally incurs additional costs related to routing and network latency. Moreover, sensor data is sent to application users on an insecure medium, which leads to data security and integrity violation. In [13], a lightweight, secure and energy-efficient fog-based routing protocol (SEFR) is proposed to minimize data latency and enhance power management. Similar to classical computer networks, IoT/WSNs also have a wide range of communication standards, protocols, or management protocols. The most important technologies such as Bluetooth, ZigBee, MQTT, LoraWAN LWM2M, 6 LowPAN are worth mentioning. However, due to resource unification limitations, IoT networks connect many problems to solve which affect their performance such as worsening of the link quality, network overloading, and device failures. Each of these factors contribute to considerably minimizingthe performance of IoT/WSNs. Therefore, it is important to effectively and proactively manage IoT networks to ensure satisfactory network performance, low latency, or good energy efficiency [14; 15; 16]. In WSNs, resource constraints are the main factor in protocols and application design. The appropriately applied routing algorithm has a direct impact on the energy consumption of the sensors. It is sometimes the most important factor in protocol decisions such as routing metrics. In Software-Defined Networking (SDN) based networks, the central node is responsible for all decisions regarding steering and routing. Taking energy as a traffic metric involves this information from the nodes, which increases packet traffic, affecting network performance [17]. The work [18] proposed an energy model for wireless sensor networks by obtaining the energy utilization at each node. This model calculates the energy at each node by evaluating the energy consumption of the core features that are involved in the detection and transfer of data during the operation of the routing protocol. This problem is considered by many researchers from the point of view of both energy and network performance metrics. As such, fault tolerance is realized as an integrated part of the IoT system design and should be built into the system. This is an essential assumption in order to find and identify different strategies that can be adapted to provide a very high level of fault tolerance to the IoT-based system. In the paper [19], the authors present an IoT/WSN implemented by the ICMC at the University of Sao Paulo (USP), called REDE, which aims to monitor, analyze data, detect flash floods, and present actual information about rivers in urban areas. The REDE system collects data about rivers and precipitation in an area and uses ZigBee and 3G to communicate.