# Minimum-Cost-Based Neighbour Node Discovery Scheme for Fault Tolerance under IoT-Fog Networks
## 1 Introduction  
The exponential growth in network traffic has led to various emerging wireless technologies such as 5G and Beyond-5G. It is anticipated that these new wireless technologies will grow in importance across multiple industries and make more strides in portable device applications. Smart home systems, productivity, animal farms, agriculture, environmental monitoring, e-health services, commercial and industrial, motor vehicles and transportation, space exploration, and wearable devices are only a few of the numerous sectors in which IoT has generated an unending number of new applications in smart cities. Everything is now easier than ever with the help of IoT-related services. In the Fog network, the data generated from the IoT/User devices are collected based on priority using big data from an urban environment [1]. The gathered data must be sent from the source to the destination for task-processing with the best possible accuracy and efficiency. Dependence on the internet and internet-based services is proliferating worldwide. The volume of data generated by such electronic devices will increase as more and more devices with internet access become a part of our daily lives. Global mobile data traffic is forecasted by ITU, which indicates that 607 Exa-Bytes (EBs) will be reached in 2025 and 5016 EBs in 2030 with M2M data. New approaches to analysing these enormous data streams are being studied. For instance, the Constrained Application Protocol (CoAP) [2] was recently developed to serve as a link between a wireless network and the global web (Internet). Additionally, sending data to the cloud will increase the time gap between a task's occurrenceand its completion. The current cloud service design is highly centralized, meaning that numerous applications can only be run in one location, called the data centre. Because of the rapid progress in cloud computing, the number of data centres is rapidly expanding. The energy demand of data centres will grow from 200 TW/h in 2018 to 2965 TW/h in 2030 [3]. Integrating the power of IoT, the Cloud, and Fog computing provides a significant opportunity to take educational institutions to the next level in terms of technology. Cloud-based data collection from sensors and learning platforms allows educators to track student progress and identify areas needing improvement. These technologies can create a more engaging, efficient, and accessible learning environment, empower educators, and improve the overall educational experience [4]. In response to these issues, Fog computing was introduced, which moves computation from the cloud to the edge device. This may result in shorter delays and less traffic to or from the cloud. A FC network allows for IoT applications by selectively finding nearby heterogeneous devices like PCs, data centres, gateways, and servers to overcome time-sensitive (high-priority) transmission and bandwidth issues [5]. One of the significant issues in FC is identifying the faults that occur in resource blocks (RBs), which act as a connecting path between an IoT layer and fog layer with multiple Fog nodes (FNs) to offload tasks among them during processing and provide reliable and fault-free transmission to all the connected IoT devices. However, identifying faulty resources is comparatively easy when determining the Fog node's fault. The resource block faults were identified and rectified with the existing OEeRA algorithm to provide effective task-offloading [6]. As an extension of the previous research, identifying the faults that occur in Fog nodes and providing a fault-free transmission is the focus of this research article. Due to the depletion of energy levels in the Fog node, neighbour node discovery is required to identify the alternate Fog nodes for reliable transmission in multi-hop Fog networks [7]. Overall, these strategies can be categorized into two categories based on whether they add efficient nodes or remove ineffective nodes.