# Reliable Fault Tolerant-Based Multipath Routing Model for Industrial Wireless Control Systems
## 1 Introduction  
Industrial wireless sensor networks (IWSNs) are a promising technology in process automation transmission, since they permit integrating the concepts of Industry 4.0 (I4.0) with the industrial Internet of Things (IIoT) [1, 2]. IWSNs have received a lot of attention because of their numerous benefits and industrial applications such as control, inventory, and monitoring systems based on obtained information to enhance productivity and offer cost reduction [3]. By 2025, the globally recognized IWSNs market is predicted to hit USD 8.67 billion [4]. IWSN benefits include flexibility, versatility, reduced infrastructure, low maintenance, and scalability [5, 6]. An IWSN is composed of access points (APs), a gateway and a collection of wireless sensor nodes. The APs link these sensor nodes to the gateway, where the latter supplies the network automation by providing the required connections to the respective plant. The gateway is attached to a device called a network manager (NM), which is in charge of network management, scheduling, routing, admission control, and setup. The use of centralized management allows for network control as well as the simplification of node hardware and software. Wireless standards such as ISA SP100.11a, WirelessHART (WH), and WIA-PA standards are widely implemented in IWSNapplications [5, 7]. These standards typically form mesh networks, with nodes acting as routers to improve communication path availability [8]. Figure 1 shows an example of WirelessHART mesh network structure. In most IWSN applications, real-time, low-latency, and reliable data communications are required [9]. Another prerequisite is low energy consumption, as batteries are frequently utilized to supply nodes [10]. One of the most basic requirements of IWSNs is to extend the network lifetime. The energy consumption of sensor nodes has the most significant impact on the network's lifetime [11]. It is often a complex mission to optimize the network performance and to meet such requirements due to the topologies' characteristics, devices, and properties of a wireless network such as signal interruption, interference, shared platform, and transmission power [10, 12]. Meanwhile, it is unpredictable in working scenarios, where interfering variables such as electromagnetic waves, vibration, and temperature might lead to network failures or faults such as operating software faults, asynchronous clock, radio frequency conflicts, depleted battery, and path losses [13, 14]. This will significantly reduce the reliability of sensor nodes, and diminish or disrupt the normal functioning of wireless networks. The network's performance has been severely hampered, and it will face significant hurdles in terms of adaptability, robustness, and reliable data transmission [15]. The reliability and accuracy of data transmission are intimately linked to successfully implement wireless networks. These concerns remain unresolved in terms of fundamental theory and engineering techniques [16]. Based on the working scenario of a network and its very own characteristics, failure of links or nodes might arise while the network process is running. These failures will have an effect on the topology stability and data transmission reliability, and consequently, degrade the overall comprehensive network performance. The network's health is crucial for wireless sensor networks to operate reliably, transmit data reliably, and optimize performance [15]  
For these reasons, it is necessary to build fault-tolerant based multi-hop and routing mechanisms that require the least amount of additional computation despite the fact that they may also require additional communication in order to construct or recover the damaged paths due to a node or link failure [17]. Network stability and reliability are improved by the use of fault tolerance methods, which employ techniques or algorithms to grant a reliable data transfer in order to increase the reliability and stability of networks [16].