Fast and Low-Overhead Time Synchronization for Industrial Wireless Sensor Networks with Mesh-Star Architecture

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.

Semantic Interconnection Scheme for Industrial Wireless Sensor Networks and Industrial Internet with OPC UA Pub/Sub

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.

Enhancing Graph Routing Algorithm of Industrial Wireless Sensor Networks Using the Covariance-Matrix Adaptation Evolution Strategy

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.

A Survey on the Application of WirelessHART for Industrial Process Monitoring and Control

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.

ISA 100.11a Networked Control System Based on Link Stability

Wireless networked control systems (WNCSs) must ensure that control systems are stable, robust and capable of minimizing the effects of disturbances. Due to the need for a stable and secure WNCS, critical wireless network variables must be taken into account in the design. As wireless networks are composed of several links, factors that indicate the performances of these links can be used to evaluate the communication system in the WNCS. This work presents a wireless network control system composed of ISA 100.11a sensors, a network manager, a controller and a wired actuator. The system controls the liquid level in the tank of the coupled tank system. In order to assess the influence of the sensor link failure on the control loop, the controller calculates the link stability and chooses an alternative link in case of instability in the current link. Preliminary tests of WNCS performance were performed to determine the minimum stability value of the link that generates an error in the control loop. Finally, the tests of the control system based on link stability obtained excellent results. Even with disturbances in the network links, the control system error remained below the threshold.

EERS: Energy-Efficient Reference Node Selection Algorithm for Synchronization in Industrial Wireless Sensor Networks

Time synchronization is an essential issue in industrial wireless sensor networks (IWSNs). It assists perfect coordinated communications among the sensor nodes to preserve battery power. Generally, time synchronization in IWSNs has two major aspects of energy consumption and accuracy. In the literature, the energy consumption has not received much attention in contrast to the accuracy. In this paper, focusing on the energy consumption aspect, we introduce an energy-efficient reference node selection (EERS) algorithm for time synchronization in IWSNs. It selects and schedules a minimal sequence of connected reference nodes that are responsible for spreading timing messages. EERS achieves energy consumption synchronization by reducing the number of transmitted messages among the sensor nodes. To evaluate the performance of EERS, we conducted extensive experiments with Arduino Nano RF sensors and revealed that EERS achieves considerably fewer messages than previous techniques, robust time synchronization (R-Sync), fast scheduling and accurate drift compensation for time synchronization (FADS), and low power scheduling for time synchronization protocols (LPSS). In addition, simulation results for a large sensor network of 450 nodes demonstrate that EERS reduces the whole number of transmitted messages by 52%, 30%, and 13% compared to R-Sync, FADS, and LPSS, respectively.

FW-PSO Algorithm to Enhance the Invulnerability of Industrial Wireless Sensor Networks Topology

When an industrial wireless sensor network (WSN) is seriously disturbed and intentionally attacked, sometimes it fails easily, even leading to the paralysis of the entire industrial wireless network. In order to improve the invulnerability of networks, in this paper, the scale-free network in complex networks is taken as the research object, and the industrial WSN with scale-free characteristics is modeled. Based on the advantages of the fireworks algorithm, such as strong searching ability and diversity of population, a so-called fireworks and particle swarm optimization (FW-PSO) algorithm is proposed, which can improve the global search ability and convergence speed effectively. The proposed FW-PSO algorithm is used to optimize the network topology and form a network with the largest natural connectivity, which can effectively promote the ability of network to resist the cascade failure problem. The dynamic invulnerability of the optimized network under highest-degree (HD) attack and lowest-degree (LD) attack strategies, as well as the static invulnerability under random attack, were evaluated respectively. Simulation experiments show that the industrial WSN optimized by FW-PSO can significantly improve the performance of the dynamic and static invulnerabilities compared with the initial network and the networks optimized by the other two existing algorithms.

Consensus-Based Sequential Estimation of Process Parameters via Industrial Wireless Sensor Networks

Process parameter estimation, to a large extent, determines the industrial production quality. However, limited sensors can be deployed in a traditional wired manner, which results in poor process parameter estimation in hostile environments. Industrial wireless sensor networks (IWSNs) are techniques that enrich sampling points by flexible sensor deployment and then purify the target by collaborative signal denoising. In this paper, the process industry scenario is concerned, where the workpiece is transferred on the belt and the parameter estimate is required before entering into the next process stage. To this end, a consensus-based sequential estimation (CSE) framework is proposed which utilizes the co-design of IWSN and parameter state estimation. First, a group-based network deployment strategy, together with a TDMA (Time division multiple access)-based scheduling scheme is provided to track and sample the moving workpiece. Then, by matching to the tailored IWSN, the sequential estimation algorithm, which is based on the consensus-based Kalman estimation, is developed, and the optimal estimator that minimizes the mean-square error (MSE) is derived under the uncertain wireless communications. Finally, a case study on temperature estimation during the hot milling process is provided. The results show that the estimation error can be reduced to less than 3 ∘ C within a limited time period, although the measurement error can be more than 100 ∘ C in existing systems with a single-point temperature sensor.

Node-Identification-Based Secure Time Synchronization in Industrial Wireless Sensor Networks

Time synchronization is critical for wireless sensors networks in industrial automation, e.g., event detection and process control of industrial plants and equipment need a common time reference. However, cyber-physical attacks are enormous threats causing synchronization protocols to fail. This paper studies the algorithm design and analysis in secure time synchronization for resource-constrained industrial wireless sensor networks under Sybil attacks, which cannot be well addressed by existing methods. A node-identification-based secure time synchronization (NiSTS) protocol is proposed. The main idea of this protocol is to utilize the timestamp correlation among different nodes and the uniqueness of a node’s clock skew to detect invalid information rather than isolating suspicious nodes. In the detection process, each node takes the relative skew with respect to its public neighbor as the basis to determine whether the information is reliable and to filter invalid information. The information filtering mechanism renders NiSTS resistant to Sybil attacks and message manipulation attacks. As a completely distributed protocol, NiSTS is not sensitive to the number of Sybil attackers. Extensive simulations were conducted to demonstrate the efficiency of NiSTS and compare it with existing protocols.

An Effective Delay Reduction Approach through a Portion of Nodes with a Larger Duty Cycle for Industrial WSNs

For Industrial Wireless Sensor Networks (IWSNs), sending data with timely style to the stink (or control center, CC) that is monitored by sensor nodes is a challenging issue. However, in order to save energy, wireless sensor networks based on a duty cycle are widely used in the industrial field, which can bring great delay to data transmission. We observe that if the duty cycle of a small number of nodes in the network is set to 1, the sleep delay caused by the duty cycle can be effectively reduced. Thus, in this paper, a novel Portion of Nodes with Larger Duty Cycle (PNLDC) scheme is proposed to reduce delay and optimize energy efficiency for IWSNs. In the PNLDC scheme, a portion of nodes are selected to set their duty cycle to 1, and the proportion of nodes with the duty cycle of 1 is determined according to the energy abundance of the area in which the node is located. The more the residual energy in the region, the greater the proportion of the selected nodes. Because there are a certain proportion of nodes with the duty cycle of 1 in the network, the PNLDC scheme can effectively reduce delay in IWSNs. The performance analysis and experimental results show that the proposed scheme significantly reduces the delay for forwarding data by 8.9~26.4% and delay for detection by 2.1~24.6% without reducing the network lifetime when compared with the fixed duty cycle method. Meanwhile, compared with the dynamic duty cycle strategy, the proposed scheme has certain advantages in terms of energy utilization and delay reduction.

Node Location Privacy Protection Based on Differentially Private Grids in Industrial Wireless Sensor Networks

Wireless sensor networks (WSNs) are widely applied in industrial application with the rapid development of Industry 4.0. Combining with centralized cloud platform, the enormous computational power is provided for data analysis, such as strategy control and policy making. However, the data analysis and mining will bring the issue of privacy leakage since sensors will collect varieties of data including sensitive location information of monitored objects. Differential privacy is a novel technique that can prevent compromising single record benefits. Geospatial data can be indexed by a tree structure; however, existing differentially private release methods pay no attention to the concrete analysis about the partition granularity of data domains. Based on the overall analysis of noise error and non-uniformity error, this paper proposes a data domain partitioning model, which is more accurate to choose the grid size. A uniform grid release method is put forward based on this model. In order to further reduce the errors, similar cells are merged, and then noise is added into the merged cells. Results show that our method significantly improves the query accuracy compared with other existing methods.

Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs' demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays.

Mixed Criticality Scheduling for Industrial Wireless Sensor Networks

Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones.