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Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: Industrial Wireless Sensor Networks (IWSNs) have gained significant popularity for their ability to improve plant productivity and production efficiency through self‐organization and rapid deployment. However, the challenge of achieving reliable and sustainable data transmission remains due to the large amount of heterogeneous data generated by large‐scale IWSNs. In this paper, we present a systematic approach that addresses this challenge by focusing on data transmission clustering strategies, optimal cluster head selection, and routing design. We propose a novel Jointly Optimized Clustering Protocol (JOCP), which enhances cluster head selection by considering multiple critical factors that impact the IWSN life cycle. JOCP incorporates two key modules: the many‐objective clustering model and the double‐layer selection evolutionary algorithm. Specifically, the many‐objective clustering model considers cluster head selection from different perspectives, including maximum node survival cycle, minimum node distance, minimum network overall energy consumption, and balanced cluster energy consumption, with the aim of extending the network life cycle. Additionally, the double‐layer selection evolutionary algorithm optimizes the many‐objective clustering model to select appropriate cluster heads. Through performance verification, we demonstrate that the JOCP protocol effectively enhances the network life cycle and increases the number of surviving nodes compared to baseline clustering algorithms. Our research provides a comprehensive solution to the challenges associated with reliable and sustainable data transmission in large‐scale IWSNs, highlighting the potential for improved performance in industrial applications. [ABSTRACT FROM AUTHOR]

Security is an important factor that cannot be neglected in the design of time synchronization algorithms since industrial wireless sensor networks are prone to attacks against physical nodes and communication links. The Sybil attack is an intelligent attack with a high destructive capacity in pretending multiple identities and broadcasting illegitimate messages to destroy the network operation. Existing secure time synchronization algorithms mostly focus on distributed protocols; however, they pay less attention to Sybil attacks and centralized network time synchronization. In this paper, we propose a novel reference broadcast-based secure time synchronization (RSTS) for industrial wireless sensor networks with a time source against Sybil attacks. Different from previous protocols, in converging the network structure and the clock status, RSTS employs a public neighbor forwarding mechanism based on reference broadcast to filter the illegal time information automatically. Instead of establishing a table with timestamps of packet transmission and receipt, the least square linear regression is utilized to estimate the compensation relative to the source node with the recorded time and calculated time difference in receiving packets. The simulation results demonstrate that RSTS is resilient to Sybil attacks as well as message manipulation attacks in comparison with existing algorithms. [ABSTRACT FROM AUTHOR]

Reliable, fast, and deterministic communications are fundamental for future industrial wireless systems. This goal requires multiple cooperating technologies that pertain to different areas of the communication arena. The weight of the waveform and coding technique choices are critical to match industrial use cases' reliability and latency requirements. Specifically, this article contributes to the field of channel coding in wireless fieldbus links. Classical block coding schemes were designed to maximize information bit rates without stringent latency requirements. Their performance in applications that use short messages degrades significantly. Recently, sparse vector coding (SVC) has been proposed as a coding approach suitable for short-packet communications with moderate complexity and low processing latency. This article presents a comprehensive analysis of SVC and a reference communication framework for its implementation on a wireless system. A set of simulations is also designed to establish the cross correlation between the different parameters involved in the code design. As a result, the coding matrix has been identified as a critical parameter that can improve coding performance. In addition, this article includes two new procedures for determining the matrix that could lead to a gain of up to 2 dB with respect to the current state of the art.

The expansion of usage of wireless technologies in sensor networks is evident in all areas, especially in the industrial sensor networks. The appliance of wireless sensor networks in industrial environments is challenging task considering the strict requirements and high performance needed for efficiency in industry monitoring and automation. The other important question is the coexistence of wireless technologies operating in 2.4 GHz band. This question becomes more important in recent years with the increased number of standards designed for this band. The research presented in this paper is focused on the performance analyses of WirelessHART technology coexisting with IEEE 802.11 technology in industrial system. The parameters observed in this study are defined with the specific industrial environment requirements. These parameters are primarily latency but the overall network performance as well. The results of the research show that WirelessHART system with a low level of latency and a low error rate at certain distances can have a successful application in the industrial system when it is operating alone. In the case of coexistence with IEEE 802.11 GHz, the WirelessHART shows the significant performance downgrade, especially latency. Besides the results, and results analyses this paper gives the description of the experimental setup in the industrial scenario. [ABSTRACT FROM AUTHOR]

Recent advances in wireless sensor networks, especially in industry (IWSN), have brought important improvements to deploy a sensor network in such environments. However, there is a high interference level, noise, shadowing, and multipath fading, caused by machines, several metallic objects, which affect the link quality. Some mechanisms have been proposed to deal with these effects, such as frequency hopping and channel blacklisting, or rather, denylisting. However, there are still open issues, such as an appropriate method for managing both mechanisms to avoid similar or adjacent channels in simultaneous transmissions. In addition to denylisting with low quality channels, this paper proposes a greylist with uncertain quality channels, and a whitelist, or rather, allowlist, with good quality channels. A fuzzy logic method to classify them and insert the channels into the appropriate list is used. The mechanism was compared to the channel hopping approach employed on the time slotted channel hopping (TSCH) protocol with and without channel offset management in tree topology networks. The evaluations were made through simulations using a realistic channel model for IWSN, and the results demonstrate that the proposed approach presented better performance in terms of packet delivery rate and determinism. In the studied examples, the network with 53 devices and with the triple channel list approach presented 8% better in terms of packet delivery rate in the application layer than the blind approach (without link quality estimation) of TSCH with channel offset management (no collision), and from 51 to 59% better than approaches without the channel offset management. [ABSTRACT FROM AUTHOR]

Low-overhead, robust, and fast-convergent time synchronization is important for resource-constrained large-scale industrial wireless sensor networks (IWSNs). The consensus-based time synchronization method with strong robustness has been paid more attention in wireless sensor networks. However, high communication overhead and slow convergence speed are inherent drawbacks for consensus time synchronization due to inefficient frequent iterations. In this paper, a novel time synchronization algorithm for IWSNs with a mesh–star architecture is proposed, namely, fast and low-overhead time synchronization (FLTS). The proposed FLTS divides the synchronization phase into two layers: mesh layer and star layer. A few resourceful routing nodes in the upper mesh layer undertake the low-efficiency average iteration, and the massive low-power sensing nodes in the star layer synchronize with the mesh layer in a passive monitoring manner. Therefore, a faster convergence and lower communication overhead time synchronization is achieved. The theoretical analysis and simulation results demonstrate the efficiency of the proposed algorithm in comparison with the state-of-the-art algorithms, i.e., ATS, GTSP, and CCTS. [ABSTRACT FROM AUTHOR]

Age of information (AoI) is an emerging network metric that measures information freshness from an application layer perspective. It can evaluate the timeliness of information in industrial wireless sensor networks (IWSNs). Previous research has primarily focused on minimizing the long-term average AoI of the entire system. However, in practical industrial applications, optimizing the average AoI does not guarantee that the peak AoI of each data packet is within a bounded interval. If the AoI of certain packets exceeds the predetermined threshold, it can have a significant impact on the stability of the industrial control system. Therefore, this paper studies the scheduling problem subject to a hard AoI performance requirement in IWSNs. First, we propose a low-complexity AoI-bounded scheduling algorithm for IWSNs that guarantees that the AoI of each packet is within a bounded interval. Then, we analyze the schedulability conditions of the algorithm and propose a method to decrease the peak AoI of nodes with higher AoI requirements. Finally, we present a numerical example that illustrates the proposed algorithm step by step. The results demonstrate the effectiveness of our algorithm, which can guarantee bounded AoI intervals (BAIs) for all nodes. [ABSTRACT FROM AUTHOR]

In the Industry 4.0 era, with the continuous integration of industrial field systems and upper-layer facilities, interconnection between industrial wireless sensor networks (IWSNs) and industrial Internet networks is becoming increasingly pivotal. However, when deployed in real industrial scenarios, IWSNs are often connected to legacy control systems, through some wired industrial network protocols via gateways. Complex protocol translation is required in these gateways, and semantic interoperability is lacking between IWSNs and the industrial Internet. To fill this gap, our study focuses on realizing the interconnection and interoperability between an IWSN and the industrial Internet. The Open Platform Communications Unified Architecture (OPC UA) and joint publish/subscribe (pub/sub) communication between the two networks are used to achieve efficient transmission. Taking the Wireless Networks for Industrial Automation Process Automation (WIA-PA), a typical technology in IWSNs, as an example, we develop a communication architecture that adopts OPC UA as a communication bridge to integrate the WIA-PA network into the industrial Internet. A WIA-PA virtualization method for OPC UA pub/sub data sources is designed to solve the data mapping problem between WIA-PA and OPC UA. Then, the WIA-PA/OPC UA joint pub/sub transmission mechanism and the corresponding configuration mechanism are designed. Finally, a laboratory-level verification system is implemented to validate the proposed architecture, and the experimental results demonstrate its promising feasibility and capability. [ABSTRACT FROM AUTHOR]

The emergence of the Industrial Internet of Things (IIoT) has accelerated the adoption of Industrial Wireless Sensor Networks (IWSNs) for numerous applications. Effective communication in such applications requires reduced end-to-end transmission time, balanced energy consumption and increased communication reliability. Graph routing, the main routing method in IWSNs, has a significant impact on achieving effective communication in terms of satisfying these requirements. Graph routing algorithms involve applying the first-path available approach and using path redundancy to transmit data packets from a source sensor node to the gateway. However, this approach can affect end-to-end transmission time by creating conflicts among transmissions involving a common sensor node and promoting imbalanced energy consumption due to centralised management. The characteristics and requirements of these networks encounter further complications due to the need to find the best path on the basis of the requirements of IWSNs to overcome these challenges rather than using the available first-path. Such a requirement affects the network performance and prolongs the network lifetime. To address this problem, we adopt a Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) to create and select the graph paths. Firstly, this article proposes three best single-objective graph routing paths according to the IWSN requirements that this research focused on. The sensor nodes select best paths based on three objective functions of CMA-ES: the best Path based on Distance (PODis), the best Path based on residual Energy (POEng) and the best Path based on End-to-End transmission time (POE2E). Secondly, to enhance energy consumption balance and achieve a balance among IWSN requirements, we adapt the CMA-ES to select the best path with multiple-objectives, otherwise known as the Best Path of Graph Routing with a CMA-ES (BPGR-ES). A simulation using MATALB with different configurations and parameters is applied to evaluate the enhanced graph routing algorithms. Furthermore, the performance of PODis, POEng, POE2E and BPGR-ES is compared with existing state-of-the-art graph routing algorithms. The simulation results reveal that the BPGR-ES algorithm achieved 87.53% more balanced energy consumption among sensor nodes in the network compared to other algorithms, and the delivery of data packets of BPGR-ES reached 99.86%, indicating more reliable communication. [ABSTRACT FROM AUTHOR]

Upgraded cloud administrations and remote innovations are altering modern industrial communications. By consolidating the advantages of distributed computing and enormously intelligent correspondence, modern remote organizations can improve framework checking and control. The need of embracing cloud computing advances for handling gigantic information from sensors is talked about in the review. A sensor network is a remote framework comprised of geologically scattered independent items that are fitted with sensors and work together to watch out for the physical and natural circumstances at different modern destinations. In this review, we make a remote cloud stage for data posting and modern climate detecting. Notwithstanding, the data should be put away using cloud computing innovation as this empowers handling, putting away, and framework organization with minimal expense virtualization and adjustment choices. An open, versatile, and inconsistent foundation for overseeing and controlling applications can be presented by distributed computing. The cloud framework is made as an independent organization that speaks with devices that use channel jumping convention. By incorporating a proactive cross layer transferring technique, the cloud stage improves industry-standard systems administration functionalities while dealing with the conveyance of information that is idleness and throughput-basic. Advantages of this framework incorporate appropriateness for any shrewd gadget can screen continuous modern data any place it is, as well as its sensible stockpiling limit and straightforward PC power. The administrators and regulators can utilize any web proficient gadget to get to our cloud administration completely.

Security is an important factor that cannot be neglected in the design of time synchronization algorithms since industrial wireless sensor networks are prone to attacks against physical nodes and communication links. The Sybil attack is an intelligent attack with a high destructive capacity in pretending multiple identities and broadcasting illegitimate messages to destroy the network operation. Existing secure time synchronization algorithms mostly focus on distributed protocols; however, they pay less attention to Sybil attacks and centralized network time synchronization. In this paper, we propose a novel reference broadcast-based secure time synchronization (RSTS) for industrial wireless sensor networks with a time source against Sybil attacks. Different from previous protocols, in converging the network structure and the clock status, RSTS employs a public neighbor forwarding mechanism based on reference broadcast to filter the illegal time information automatically. Instead of establishing a table with timestamps of packet transmission and receipt, the least square linear regression is utilized to estimate the compensation relative to the source node with the recorded time and calculated time difference in receiving packets. The simulation results demonstrate that RSTS is resilient to Sybil attacks as well as message manipulation attacks in comparison with existing algorithms.

The diffusion of toxic gas, biochemical material, and radio-active contamination – known as continuous objects – endangers the safe production of the petrochemical and nuclear industries. To mitigate these well known hazards, the new paradigm of industrial wireless sensor networks (IWSNs) shows great potential in monitoring evolving hazardous phenomena in unfriendly industrial fields. In order to prolong the lifetime of these networks, existing research focuses on energy-efficient boundary nodes selection. However, sensor state cannot be scheduled proactively, due to the difficulty in predicting the spatiotemporal evolution of diffusive hazards. In this article, we propose a motion behavior learning predictive tracking (MBLPT) algorithm for continuous objects in IWSNs. Considering the relatively unpredictable patterns exhibited by continuous objects, the MBLPT uses a data-driven approach for motion state recognition, and then utilizes Bayesian model averaging (BMA) for future boundary prediction. The prediction of the MBLPT provides the knowledge for establishing a wake-up zone, in which standby nodes are activated in advance to participate in tracking the upcoming boundary. Simulation results demonstrate that the MBLPB achieves superior energy efficiency while keeping effective tracking accuracy. [ABSTRACT FROM AUTHOR]

Privacy and security are the key issues in Industrial Wireless Sensor Networks (IWSN) as the wireless sensor nodes are typically deployed in a hostile environment (i.e., in a remote location where minimum or no human intervention is required) and can be easily compromised by an attacker. Several protocols have been proposed to address these issues. However, none of them can fulfill the required privacy and security goals. Additionally, the traditional network architecture presents a performance bottleneck due to the rapidly increasing traffic volume and heterogeneous sensor nodes. Hence, the existing architecture needs to be upgraded accordingly. In this article, we propose a Software-Defined Networking (SDN)-based authentication protocol for real-time data transfer in IWSN, called SDIWSN. SDIWSN puts the management and control functions of the network into a set of logically centralized SDN controllers, thus providing a global view of the network. SDIWSN achieves several privacy and security requirements such as anonymity, unlinkability, mutual authentication, key agreement, forward secrecy and robustness against passive and active attacks. Moreover, SDIWSN provides a simple velocity-based strategy to detect cloning attacks. We validate the privacy and security features of SDIWSN using formal and informal verification. Finally, the efficiency of SDIWSN is measured through a performance-based comparison. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Low-overhead, robust, and fast-convergent time synchronization is important for resource-constrained large-scale industrial wireless sensor networks (IWSNs). The consensus-based time synchronization method with strong robustness has been paid more attention in wireless sensor networks. However, high communication overhead and slow convergence speed are inherent drawbacks for consensus time synchronization due to inefficient frequent iterations. In this paper, a novel time synchronization algorithm for IWSNs with a mesh–star architecture is proposed, namely, fast and low-overhead time synchronization (FLTS). The proposed FLTS divides the synchronization phase into two layers: mesh layer and star layer. A few resourceful routing nodes in the upper mesh layer undertake the low-efficiency average iteration, and the massive low-power sensing nodes in the star layer synchronize with the mesh layer in a passive monitoring manner. Therefore, a faster convergence and lower communication overhead time synchronization is achieved. The theoretical analysis and simulation results demonstrate the efficiency of the proposed algorithm in comparison with the state-of-the-art algorithms, i.e., ATS, GTSP, and CCTS.

As industrialization accelerates, the industrial sensor network environment becomes more complex. Hierarchical multi-cluster wireless sensing network topology is generally used due to large-scale industrial environments, harsh environments, and data overload impact. In industrial wireless sensor networks, the overload of some nodes may lead to the failure of the whole network, which is called cascading failure. This phenomenon has incalculable impact on industrial production. However, cascading failure models have mainly been studied for planar structures, and there is no cascading failure model for hierarchical topologies in industrial environments. Therefore, this paper built a cascading failure model for hierarchical industrial wireless sensor networks (IWSNs) for realistic industrial network topologies. By establishing an evaluation mechanism considering the efficiency of the network and the viability of nodes, the network communication efficiency that is not considered in the traditional evaluation mechanism is solved. In addition, aiming at the problem of network topology changes caused by node failure, dynamic load distribution methods (ADD, SLD) are used to improve network invulnerability. Theoretical analysis and experimental results show that the traditional allocation method (SMLD) does not apply in hierarchical topologies; when the general cluster head node capacity is moderate, increasing the capacity of single-hop cluster head nodes can prevent cascading failures more effectively. [ABSTRACT FROM AUTHOR]

Due to the flammability, explosiveness and toxicity of continuous objects (e.g., chemical gas, oil spill, radioactive waste) in the petrochemical and nuclear industries, boundary tracking of continuous objects is a critical issue for industrial wireless sensor networks (IWSNs). In this article, we propose a continuous object boundary tracking algorithm for IWSNs – which fully exploits the collective intelligence and machine learning capability within the sensor nodes. The proposed algorithm first determines an upper bound of the event region covered by the continuous objects. A binary tree-based partition is performed within the event region, obtaining a coarse-grained boundary area mapping. To study the irregularity of continuous objects in detail, the boundary tracking problem is then transformed into a binary classification problem; a hierarchical soft margin support vector machine training strategy is designed to address the binary classification problem in a distributed fashion. Simulation results demonstrate that the proposed algorithm shows a reduction in the number of nodes required for boundary tracking by at least 50 percent. Without additional fault-tolerant mechanisms, the proposed algorithm is inherently robust to false sensor readings, even for high ratios of faulty nodes ($\approx 9\%$ ≈ 9 % ). [ABSTRACT FROM AUTHOR]

Industrial Wireless Sensor Network (IWSN) includes numerous sensor nodes that collect data about target objects and transmit to sink nodes (SN). During data transmission among nodes, intrusion detection is carried to improve data security and privacy. Intrusion detection system (IDS) examines the network for intrusions based on user activities. Several works have been done in the field of intrusion detection and different measures are carried out to increase data security from the issues related to black hole, Sybil attack, Worm hole, identity replication attack and etc. In various existing approaches, secure data transmission is not achieved, therefore resulted in compromising the security and privacy of IWSNs. Accurate intrusion detection is still challenging task in terms of improving security and intrusion detection rate. In order to improve intrusion detection rate (IDR) with minimum time, generalized Frechet Hyperbolic Deep and Dirichlet Secured (FHD-DS) data communication model is introduced. At first, Frechet Hyperbolic Deep Traffic (FHDT) feature extraction method is designed to extract more relevant network activities and inherent traffic features. With the help of extracted features, anomalous or normal data is predicted. Followed by Statistical Dirichlet Anomaly-based Intrusion Detection model is applied to discover intrusion. Here, Dirichlet distribution is evaluated to attain secure data transmission and significantly detect intrusions in WSNs. Experimental evaluation is carried out with KDD cup 99 dataset on factors such as IDR, intrusion detection time (IDT) and data delivery rate (DDR). The observed results show that the generalized FHD-DS data communication method achieves higher IDR with minimum time. [ABSTRACT FROM AUTHOR]

In the Industry 4.0 era, with the continuous integration of industrial field systems and upper-layer facilities, interconnection between industrial wireless sensor networks (IWSNs) and industrial Internet networks is becoming increasingly pivotal. However, when deployed in real industrial scenarios, IWSNs are often connected to legacy control systems, through some wired industrial network protocols via gateways. Complex protocol translation is required in these gateways, and semantic interoperability is lacking between IWSNs and the industrial Internet. To fill this gap, our study focuses on realizing the interconnection and interoperability between an IWSN and the industrial Internet. The Open Platform Communications Unified Architecture (OPC UA) and joint publish/subscribe (pub/sub) communication between the two networks are used to achieve efficient transmission. Taking the Wireless Networks for Industrial Automation Process Automation (WIA-PA), a typical technology in IWSNs, as an example, we develop a communication architecture that adopts OPC UA as a communication bridge to integrate the WIA-PA network into the industrial Internet. A WIA-PA virtualization method for OPC UA pub/sub data sources is designed to solve the data mapping problem between WIA-PA and OPC UA. Then, the WIA-PA/OPC UA joint pub/sub transmission mechanism and the corresponding configuration mechanism are designed. Finally, a laboratory-level verification system is implemented to validate the proposed architecture, and the experimental results demonstrate its promising feasibility and capability.

The emergence of the Industrial Internet of Things (IIoT) has accelerated the adoption of Industrial Wireless Sensor Networks (IWSNs) for numerous applications. Effective communication in such applications requires reduced end-to-end transmission time, balanced energy consumption and increased communication reliability. Graph routing, the main routing method in IWSNs, has a significant impact on achieving effective communication in terms of satisfying these requirements. Graph routing algorithms involve applying the first-path available approach and using path redundancy to transmit data packets from a source sensor node to the gateway. However, this approach can affect end-to-end transmission time by creating conflicts among transmissions involving a common sensor node and promoting imbalanced energy consumption due to centralised management. The characteristics and requirements of these networks encounter further complications due to the need to find the best path on the basis of the requirements of IWSNs to overcome these challenges rather than using the available first-path. Such a requirement affects the network performance and prolongs the network lifetime. To address this problem, we adopt a Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) to create and select the graph paths. Firstly, this article proposes three best single-objective graph routing paths according to the IWSN requirements that this research focused on. The sensor nodes select best paths based on three objective functions of CMA-ES: the best Path based on Distance (PODis), the best Path based on residual Energy (POEng) and the best Path based on End-to-End transmission time (POE2E). Secondly, to enhance energy consumption balance and achieve a balance among IWSN requirements, we adapt the CMA-ES to select the best path with multiple-objectives, otherwise known as the Best Path of Graph Routing with a CMA-ES (BPGR-ES). A simulation using MATALB with different configurations and parameters is applied to evaluate the enhanced graph routing algorithms. Furthermore, the performance of PODis, POEng, POE2E and BPGR-ES is compared with existing state-of-the-art graph routing algorithms. The simulation results reveal that the BPGR-ES algorithm achieved 87.53% more balanced energy consumption among sensor nodes in the network compared to other algorithms, and the delivery of data packets of BPGR-ES reached 99.86%, indicating more reliable communication.

Abstract The Internet of Things (IoT) is the latest Internet development, with billions of Internet-connected devices and a wide range of industrial applications. Wireless sensor networks are an important part of the Internet of Things. It has received extensive attention from researchers due to its large-scale, self-organizing, and dynamic characteristics and has been widely used in industry, traffic information, military, environmental monitoring, and so on. With the development of microprocessor technology, sensor nodes are becoming more and more powerful, which enables the same wireless sensor networks (WSNs) platform to meet the different quality of service (QoS) requirements of many applications. Applications for industrial wireless sensor networks range from lower physical layers to higher application layers. The same wireless sensor network sometimes needs to process information from different layers. Traditional protocols lack differentiated services and cannot make full use of network resources. In this paper, an Adaptive Retransmit Mechanism for Delay Differentiated Services (ARM-DDS) scheme is proposed to meet different levels of delays of applications. Firstly, we analyze the impact of different retransmit mechanisms and parameter optimization on delays and energy consumption. Based on the results of the analysis, in ARM-DDS scheme, for routes with transmission delay tolerance, energy-saving retransmission mechanisms are used, and low-latency retransmission mechanisms are used for latency-sensitive routes. In this way, the data routing delays of different applications are guaranteed within bound and the energy consumption of the network is reduced. What is more, ARM-DDS scheme makes full use of the residual energy of the network and uses a small delay routing retransmit mechanism in the far-sink area to reduce end-to-end delay. Both theoretical analysis and simulation experiments show that under the premise of the same reliability requirements, ARM-DDS scheme reduces data transmission delay 12.1% and improves network energy utilization 28%. Given that the reliability requirements of the data stream are different, the scheme can also extend the network lifetime.

Abstract Industrial wireless sensor network (IWSN) has changed the information transmission way for existing industrial control system. In mobile sink-based industrial wireless sensor networks, the energy consumption optimization for data collection has always been a hot research issue. To meet the delay requirements and minimize energy consumption, a data collection strategy based on ant colony optimization with mobile sink is proposed for industrial wireless sensor networks. Firstly, in order to reduce the number of nodes directly accessed by sink and shorten the traversed path, the selection of rendezvous nodes based on entropy weight method is introduced according to the density of nodes, relative residual energy, and the degree of uniformity of distribution. Then, secondly, an ant colony optimization algorithm is proposed to obtain the optimal access path for mobile sink, which can achieve a trade-off between the energy consumption of the network and transmission delay. The simulation results show that, compared with the existing algorithms, the proposed algorithm can minimize the delay and prolong the lifetime of the network.

In Industrial Wireless Sensor Networks (IWSNs), monitoring data generated by field devices are supposed to be delivered to the gateway with high reliability and low latency. However, most of the existing industrial wireless standards are based on IEEE 802.15.4, offering a very limited data rate, which prevents their adoption in critical industrial applications. Based on IEEE 802.11, a recent international standard WIA-FA is proposed to address higher communication requirements in factory automation. In this paper, we study the timeslot allocation for retransmissions in the WIA-FA network. Specifically, we first design a novel superframe to support the Negative ACKnowledgment (NACK)-based retransmission mode in the WIA-FA network, and build a network model which considers the uplink and downlink packet losses simultaneously. Then, we analyze the three major drawbacks of the default NACK-based retransmission scheme in WIA-FA and propose an Automatic On-Demand Retransmission (AODR) scheme. Finally, we give a detailed reliability analysis of the proposed AODR scheme, and prove the relationship between the transmission reliability and critical factors (e.g., the channel condition and the length of the superframe) in the WIA-FA network. Simulation results show that the proposed AODR scheme outperforms existing works in terms of transmission reliability and timeliness for different channel conditions. [ABSTRACT FROM AUTHOR]

The physical layer authentication, particularly the channel state information approaches, has attracted significant research efforts due to the low computational complexity that makes it a promising solution to provide the security requirements of industrial internet of things and cyber physical systems applications. In the literature, the generalized likelihood ratio test and its many variations have been used to measure the similarity between two channel estimates'. In contrast to the previous research, this paper presents a novel physical layer authentication mechanism based on the time reversal resonating strength of the channel frequency response to formulate the binary hypothesis test of the physical layer authentication. The authentication performance of the proposed time reversal resonating strength based physical layer authentication method is evaluated using real industrial wireless system radio propagation measurements dataset. The simulation results have demonstrated the superior performance of the proposed scheme for detecting the spoofing attack while maintaining minimum false alarm rate when compared with other state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As industrialization accelerates, the industrial sensor network environment becomes more complex. Hierarchical multi-cluster wireless sensing network topology is generally used due to large-scale industrial environments, harsh environments, and data overload impact. In industrial wireless sensor networks, the overload of some nodes may lead to the failure of the whole network, which is called cascading failure. This phenomenon has incalculable impact on industrial production. However, cascading failure models have mainly been studied for planar structures, and there is no cascading failure model for hierarchical topologies in industrial environments. Therefore, this paper built a cascading failure model for hierarchical industrial wireless sensor networks (IWSNs) for realistic industrial network topologies. By establishing an evaluation mechanism considering the efficiency of the network and the viability of nodes, the network communication efficiency that is not considered in the traditional evaluation mechanism is solved. In addition, aiming at the problem of network topology changes caused by node failure, dynamic load distribution methods (ADD, SLD) are used to improve network invulnerability. Theoretical analysis and experimental results show that the traditional allocation method (SMLD) does not apply in hierarchical topologies; when the general cluster head node capacity is moderate, increasing the capacity of single-hop cluster head nodes can prevent cascading failures more effectively.

Abstract The deployment of wireless sensor networks, or WSNs, in industrial domains has attracted much attention over the past few years. An increasing number of applications have been developed such as for condition monitoring in the railway industry. Nevertheless, compared with traditional WSNs, the industrial environment is harsher, noisier, and more complex, which poses a higher requirement for the network security especially in terms of data trustiness and which further deters WSN practical integration in industrial applications. The main contribution of this research is to partially address the security issues by means of providing trusted data for industrial WSNs. To this end, a negative binomial distribution-based trust scheme combined with the D–S belief theory and a noise filter method is proposed and designed for industrial WSNs. In this paper, we first discuss the trust theory in WSNs and the disadvantages of traditional trust schemes for industrial applications, then analyze and evaluate the proposed method, and finally compare the performance of our method with some classic trust schemes. Through simulation tests about temperature readings of a factory workshop, it shows that the proposed method can improve the data trustiness, reliability, and robustness in the trust evaluation process under industrial environments and ensure the security of the network.

Abstract Location data associated with wireless sensor networks represents critical information. Current developments in localization algorithms employed in industrial wireless sensor networks seek to adopt positioning methods that are more robust and stable, and more accurate and efficient while requiring a minimum of resources. Therefore, the present study capitalizes on the industrial wireless sensor network that has a strong correlation between applications to propose a positioning method design based on a Monte Carlo localization algorithm that is ideally suited to the narrow channel environment encountered in underground mining activities. The proposed positioning method offers very low computational complexity, which greatly reduces the use of network resources. Simulation experiments demonstrate that the proposed Monte Carlo localization algorithm provides strong stability and relatively high positioning accuracy.

Abstract Industrial wireless sensor networks (IWSNs) have been widely used in many application scenarios, and data collection is an extremely significant part of IWSNs. Moreover, a mobile sink is widely used in industrial wireless sensor networks to collect sensory data and alleviate the “hot spot” problem effectively. However, usage of a mobile sink introduces some challenges, such as updating of a mobile sink’s location and planning of a mobile sink’s trajectory. Meanwhile, the impact of different distribution types of events on data collection has not been sufficiently valued in designing of data collection algorithm for IWSNs yet. To overcome these challenges, a virtual grid-based real-time data collection algorithm for applications with centrally distributed events (VGDCA-C) is proposed in this paper to gain a reliable data gathering for IWSNs. In the target application scenarios, the events are distributed centrally, so we mainly focus on how to shorten the routing paths and decrease the transmission delay. In our VGDCA-C, a mobile sink can adjust its movement dynamically according to the changes in event areas. The adjustment of a mobile sink movement strategy includes two aspects. The first one is the dynamic adjustment of a mobile sink’s parking time, and the second one denotes the moving toward event area of a mobile sink. Thus, a mobile sink adjusts its location such that it can get closer to the event area. Hence, the total length of routing is getting shorter so that source nodes can upload sensory data faster. Analysis and simulation results show that compared with the existing work, our VGDCA-C increases the network lifetime and decreases transmission delay.

Abstract Low delay and long lifetime are a very important issue for industrial wireless sensor networks (IWSNs) in which it require long-time monitoring of industrial sites and respond quickly to events that is monitored; therefore, high delay communications can cause serious damage to property and personnel at industrial field. Due to delay, lifetime, and other performance involved to multiple layers, it is difficult to optimize from a single layer. Therefore, a cross-layer design optimal scheme for reducing delay and maximizing lifetime (RDML) scheme is proposed for IWSNs which is from several layers such as transmitted power, duty cycle, and node deployment positions to optimize the network performance of delay and lifetime etc. Firstly, due to the node which sends a packet within a cycle, different duty cycle leads to different selection of the modulation level, resulting in different power consumption efficiency of transmitting data. Through careful analysis, the optimal value of the duty cycle is given which has the lowest energy consumption per bit. In fact, the energy consumption of the node is not balanced. Therefore, an optimization method of changing the duty cycle is proposed. In this paper, larger duty cycle is chosen for nodes with residual energy to improve the reliability of data transmission, reducing the probability of data retransmission, so that the network delay can be reduced in IWSNs. Third, based on the previous analysis, a network optimization deployment algorithm is proposed, which not only maximizes the energy efficiency of a single node but also maximizes the network lifetime and the total network energy efficiency. Both our comprehensive theoretical analysis results indicate that the performance of RDML scheme is better than the previous studies. Relative to equal distance and optimal duty cycle scheme, the RDML scheme can reduce the delay by 19–30% and increase the lifetime by more than 43%.

Industrial wireless sensor networks (IWSNs) are used to acquire sensor data that need realtime processing, therefore they require predictable behavior and real-time guarantees. To be cost effective, IWSNs are also expected to be low cost and low power. In this context, Bluetooth low energy (BLE) is a promising technology, as it allows implementing low-cost industrial networks. As BLE is a shortrange technology, a multihop mesh network is needed to cover a large area. Nevertheless, the recently published Bluetooth mesh networking specifications do not provide support for real-time communications over multihop mesh networks. To overcome this limitation, this paper proposes the multihop real-time BLE (MRT-BLE) protocol, a real-time protocol developed on top of BLE, that allows for bounded packet delays over mesh networks. MRT-BLE also provides priority support. This paper describes in detail the MRT-BLE protocol and how to implement it on commercial-off-the-shelf devices. Two kinds of performance evaluation for the MRT-BLE protocol are provided. The first one is a worst case end-to-end delay analysis, while the second one is based on the experimental results obtained through measurements on a real testbed.

Industrial WSNs are gradually gaining space in industry due to low cost of installation and maintenance. However, RF communications systems are prone to several propagation phenomena which can compromise reliability in terms of missed message deadlines. This work aims to increase the robustness of industrial WSN. In order to achieve this goal, it is necessary to correct inherent problems in wireless communications, some of which are channel noise, interference, and multipath fading. Multipath can be considered the main factor that makes communications in wireless sensor networks a real challenge when compared to other types of mediums, such as optical fiber, cable, or even directional radio transmissions. In this sense, antenna diversity is proposed as a solution to deal with these effects, with the aim of improving radio reliability to make the use of dense industrial WSN feasible. The potential of antenna diversity in WSN is not fully exploited in industrial applications. This article presents the combination of selection technique for industrial WSN through an algorithm that selects the transceiver port that has the highest link quality indicator and performs antenna switching in the radio modules. The results obtained are analyzed to verify the diversity gain by using antenna spatial diversity at reception and thus reduce packet error rate. The results corroborate with theory by increasing radio reliability in terms of diversity gain, quadrupling the received signal power when the correct antenna is chosen. [ABSTRACT FROM AUTHOR]

The emergence of Industry 4.0 technologies, such as the Internet of Things (IoT) and Wireless Sensor Networks (WSN), has prompted a reconsideration of methodologies for network security as well as reducing operation and maintenance costs, especially at the physical layer, where the energy consumption plays an important role. This article demonstrates through simulations and experiments that, while the cooperative scheme is more efficient when a WSN is at normal operating conditions, the collaborative scheme offers more enhanced protection against the aggressiveness of jamming in the performance metrics, thus making it safer, reducing operation and maintenance costs and laying the foundations for jamming mitigation. This document additionally offers an algorithm to detect jamming in real time. Firstly, it examines the characteristics and damages caused by the type of aggressor. Secondly, it reflects on the natural immunity of the WSN (which depends on its node density and a cooperative or collaborative configuration). Finally, it considers the performance metrics, especially those that impact energy consumption during transmission.

Industrialization has led to a huge demand for a network control system to monitor and control multi-loop processes with high effectiveness. Due to these advancements, new industrial wireless sensor network (IWSN) standards such as ZigBee, WirelessHART, ISA 100.11a wireless, and Wireless network for Industrial Automation-Process Automation (WIA-PA) have begun to emerge based on their wired conventional structure with additional developments. This advancement improved flexibility, scalability, needed fewer cables, reduced the network installation and commissioning time, increased productivity, and reduced maintenance costs compared to wired networks. On the other hand, using IWSNs for process control comes with the critical challenge of handling stochastic network delays, packet drop, and external noises which are capable of degrading the controller performance. Thus, this paper presents a detailed study focusing only on the adoption of WirelessHART in simulations and real-time applications for industrial process monitoring and control with its crucial challenges and design requirements.

The open nature of radio propagation makes wireless transmissions exposed to unauthorized users and become vulnerable to both the jamming and eavesdropping attacks. In industrial environments, wireless transmissions are also adversely affected by the presence of large-bodied obstructing machinery, metallic friction-induced impairments, and equipment noise. This may result in the failure of wireless transmissions and thus wastes the precious energy resources for industrial wireless sensor networks (IWSNs). This paper is motivated to present a review on the challenges and solutions of improving the physical-layer security and reliability for IWSNs. We first discuss some wireless reliability enhancement techniques for mitigating the background interference, path loss, multipath fading, and link failure. Then, we provide an overview of wireless jamming and eavesdropping attacks along with their countermeasures, where a jammer attempts to emit an interfering radio signal for disrupting the desired communications between a wireless sensor and its sink, while an eavesdropper intends to tap the confidential sensor-sink transmissions. Additionally, we evaluate the tradeoff between the security and reliability, called security-reliability tradeoff, in the context of wireless sensor-sink transmissions. Finally, we discuss a range of open challenges and future trends for IWSNs, including the energy-efficient security and reliability designs, joint jamming-and-eavesdropping defense mechanisms, as well as the energy harvesting for IWSNs.

In industrial wireless sensor networks (IWSNs), monitoring data generated by field devices (FDs) are supposed to be delivered to the gateway timely and reliably. The previous researches focus on the convergecast problem based on the global available channel set, where unreliable channels are blacklisted. However, in practical industrial environment, different links may have different local available channel sets (LACSs) due to the location-dependent characteristics of wireless channels. In this paper, we study the LACSs-based convergecast scheduling problem in the IWSNs with tree topologies. First, we formulate the convergecast scheduling problem in a mathematically precise form of integer programming. Then, we propose a novel method to calculate priorities for each FD, and design two effective heuristic rules of allocating channels to FDs to maximize the number of concurrent transmissions in each time slot, considering the priority of each FD and the constraints in the integer programming formulation. Finally, inspired by the proposed heuristic rules, we propose an LACSs-based convergecast scheduling (LCS) algorithms to generate efficient schedules for IWSNs in polynomial time. The simulation results show that the proposed algorithm outperforms existing works in terms of latency for different scenarios. [ABSTRACT FROM AUTHOR]

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Industry 4.0 will interconnect and digitalize traditional industries to enable smart and adaptable factories that efficiently utilize resources and integrate systems. A key enabler of this paradigm is the communications infrastructure that will support the ubiquitous connectivity of cyber-physical production systems. The integration of wireless networks will facilitate the dynamic reconfiguration of the factories of the future, and the collection and management of large amounts of data. This vision requires reliable and low latency wireless links with the necessary bandwidth to support data intensive applications and spatio-temporal variations of data resulting from the reconfiguration of Industrial IoT (Internet of Things) systems. To this aim, this paper proposes a load balancing scheme that dynamically manages the wireless links based on their quality and the amount of data to be transmitted by each node. The proposed scheme avoids the saturation of channels, and significantly augments the reliability of industrial wireless networks in comparison with existing solutions. [ABSTRACT FROM AUTHOR]

In an industrial production process, the leakage of continuous objects poses a serious threat to production safety. In this paper, a diffusion distance-based predictive tracking algorithm is proposed for industrial wireless sensor networks (IWSNs), aiming to timely track the boundary of a continuous object after the occurrence of a leak. Based on the assumption that the motion of the continuous object follows an appropriate diffusion model, sensor nodes are able to capture environmental parameters for establishing the mathematical expression of the model locally. Through building up the relation of diffusion radius with time, each node predicts diffusion scope of the continuous object at different times and makes a judgment about whether it is suitable to be a boundary node. Moreover, to achieve high energy-efficiency, a sleep/wake cycle is introduced to involve a small number of nodes in the process of tracking, while the rest of nodes stay idle until an object approaches. Finally, a cluster-based competitive mechanism is proposed for reporting the location of boundary nodes. Simulation results demonstrated that our proposal is able to track the diffusion of continuous objects with high energy-efficiency. [ABSTRACT FROM AUTHOR]

Industrial wireless sensor networks are becoming popular for critical monitoring and control applications in industrial automation systems. For such type of applications, providing reliable real-time performance regarding data delivery is considered as a fundamental challenge. The problem becomes more prominent with mixed-criticality systems, where different data flow with different levels of criticality (importance) coexist and characterized by different requirements regarding delay and reliability. In this paper, we propose a wireless fieldbus protocol to enable real-time communication and service differentiation for cluster-based mixed-criticality networks. A process monitoring scenario of plastic extrusion is used to define the protocol requirements and elaborate the working principle of the proposed work. In our proposed protocol, each data flow is scheduled for channel access based on its criticality level using a distributed prioritized medium access mechanism that ensures a guaranteed channel access for the most critical traffic over other traffic types. The performance of the proposed protocol is analyzed analytically using a discrete-time Markov chain model to evaluate the performance in terms of delay and throughput. Moreover, the extensive simulations are conducted to prove the analytical claims and different performance assessments are provided, which also demonstrate the effectiveness of the proposed approach compared with the related existing work. [ABSTRACT FROM AUTHOR]