# Modeling and Fault Tolerance Analysis of ZigBee Protocol in IoT Networks
## 1 Introduction
In order to protect the cloud from intruders, a virtualized network intrusion detection system (also known as the Networked Intrusion Detection System-Virtual Appliance, NIDS-VA) can be used to protect cloud environments such as Iaa5 infrastructure when sharing resources with other cloud applications [4], and in [5], an analysis of threats and their impact on IoT infrastructure performance and security development prospects for the near future was performed. In [6], the authors presented the concepts of Fog of Things (FoT), an on-demand IoT paradigm. Using such a solution, heterogeneous connected devices can be accessed and managed through a unified platform based on real-time requirements. The FoT paradigm includes the incorporation of fog computing power that enhances not only IoT applications but, more importantly, scalable and efficient management of the system itself. The aspect of power supply, its reliability, and especially energy-efficient protocols is equally important in ensuring the security of IoT networks. Hence, one of the essential concerns of the IoT is the energy requirements for devices. In [7], a framework is presented to provide adequate security and privacy while supporting efficient power management. The proposed framework utilizes an identity-based protection methodology (I-ICAAAN), secure communication protocols, and an Intelligent Security System for Energy Management (ISSEM) to certify security and privacy in the EI (Energy Internet). Fault tolerance is an important point in the field of ensuring uninterrupted and failure-free operation of the entire IoT system. Fault tolerance may be implemented at various levels of the IoT architecture since an error can occur at any layer. Naturally, the level of network connectivity, as well as root nodes, is critical. Infrastructure, application, and secure Internet of Things (IoT) solutions are creating new efficiencies and enabling more efficient operations based on data collected at the intelligent network edge. Production downtime and operational risk is reduced. Industrial IoT solutions enable the collection and analysis of data captured from networked assets, people, and places, resulting in meaningful analytical insights in an industrial environment and beyond. The significant cost and complexity of the infrastructure cause that there is often a lack of redundancy during deployment which makes fault tolerance in IoT an important issue. Therefore, providing fault tolerance using a limited set of devices is a major challenge for IoT system design. In [8], the authors have prepared a very comprehensive and up-to-date literature review on faults that can arise at all levels of the architecture of IoT applications, such as sensor nodes, actuators, network links, as also processing and data storage components. The presented examples clearly show that fault-tolerance (FT) has become an important concern for IoT systems. Significantly, this work provides a basis for classifying existing and future approaches to fault-tolerant IoT, by classifying a set of methodologies, techniques, and architectures that are able of reducing failures in IoT systems. A kind of evolution of IoT architectures is Edge computing. In [9], the authors proposed a new mobile agent (MA) based, reliable, and fault-tolerant hierarchical IoT cloud architecture that can cope with edge server failures. In the proposed architecture, the cloud is distributed in four tiers (cloud-fog-mist-dew) based on the computational power and distance from the end IoT device. The process of replication of the data at the network edge makes the whole system reliable. The analyzed system is fault-tolerant as it redirects the application to an optional server. The enormous increase in the amount of data transmitted by various devices makes these systems a target for various types of attacks by hackers. Monitoring network traffic is a key task for the security and reliability of communication networks and Internet of Things infrastructure.