Abstract
Communication in industrial wireless networks necessitates reliability and precision. Besides, the existence of interference or traffic in the network must not affect the estimated network properties. Therefore, data packets have to be sent within a certain time frame and over a reliable connection. However, the working scenarios and the characteristics of the network itself make it vulnerable to node or link faults, which impact the transmission reliability and overall performance. This article aims to introduce a developed multipath routing model, which leads to cost-effective planning, low latency and high reliability of industrial wireless mesh networks, such as the WirelessHART networks. The multipath routing model has three primary paths, and each path has a backup node. The backup node stores the data transmitted by the parent node to grant communication continuity when primary nodes fail. The multipath routing model is developed based on optimal network planning and deployment algorithm. Simulations were conducted on a WirelessHART simulator using Network Simulator (NS2). The performance of the developed model is compared with the state-of-the-art. The obtained results reveal a significant reduction in the average network latency, low power consumption, better improvement in expected network lifetime, and enhanced packet delivery ratio which improve network reliability.
Highlights
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]
The proposed multipath routing (MPR) model shown in Section 3.3 was applied to Kunzel, Han, and Q-Learning reliable routing (QLRR) algorithms to produce MPRKunzel, MPRHan, and MPRQLRR, respectively
The performance of the proposed model was compared with the original algorithm by evaluating average network latency (ANL), expected network lifetime (ENL), and packet delivery rate (PER)
Summary
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]. 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 IWSN applications [5,7]. These standards typically form mesh networks, with nodes acting as routers to improve communication path availability [8]. 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]. 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]
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