Industrial Wireless Research Articles

In-Band Network Telemetry in Industrial Wireless Sensor Networks

With the emergence of the Internet of Things (IoT) and Industry 4.0 concepts, industrial applications are going through a tremendous change that is imposing increasingly diverse and demanding network dynamics and requirements with a wider and more fine-grained scale. Therefore, there is a growing need for more flexible and reconfigurable industrial networking solutions complemented with powerful monitoring and management functionalities. In this sense, this paper presents a novel efficient network monitoring and telemetry solution for Industrial Wireless Sensor Networks mainly focusing on the 6TiSCH Network stack, a complete protocol stack for ultra-reliable ultra-low-power wireless mesh networks. The proposed monitoring solution creates a flexible and powerful in-band network telemetry design with minimized resource consumption and communication overhead while supporting a wide range of monitoring operations and strategies for dealing with various network scenarios and use cases. Besides, the technical capabilities and characteristics of the proposed solution are evaluated via a real-life implementation, practical and theoretical analysis. These experiments demonstrate that in-band telemetry can provide ultra-efficient network monitoring operations without any effect on the network behavior and performance, validating its suitability for Industrial Wireless Sensor Networks.

Optimisation‐based time slot assignment and synchronisation for TDMA MAC in industrial wireless sensor network

Wireless sensor network in the industrial environment [industrial wireless sensor network (IWSN)] has data delivery time constraint. Due to the dynamic routing and transmission collision, the data delivery time is unpredictable. The authors utilised time division multiple access (TDMA) MAC to avoid data collision and to provide bounded transmission delay. Moreover, a linear programming model is proposed to construct the TDMA schedules, which is focused on spatial reuse and fixed routing in IWSN. The objective function of the model is to minimise the time slot usage to increase the overall network bandwidth. Finally, both simulated annealing algorithm and particle swarm optimisation are applied to approximate the optimal solution of time slot usage.

Reliability evaluation of point-to-point links based on IEEE 802.15.4 physical layer for IWSAN applications

The reliability of point-to-point links for Industrial Wireless Sensor Networks (IWSN) based on the IEEE 802.15.4 physical layer (PHY) and operating in the unlicensed 2.45 GHz radio band is studied in this paper. An in‐lab methodology based on channel emulation is used. The IEEE 802.15.4 PHY is tested under different wireless channels: additive white Gaussian noise (AWGN), Rician, Rayleigh, and the IEEE 802.15.4a non‐line of sight (NLoS) industrial channel. The metrics used to evaluate the reliability are the packet error rate (PER) and the distribution of packet error burst (PEB). Reliability results are presented and compared with the reliability requirements of typical industrial use cases. Two mathematical expressions are also obtained to predict PER and distribution of PEB as a function of the RMS Delay Spread (RDS).

A Framework of Priority-Aware Packet Transmission Scheduling in Cluster-Based Industrial Wireless Sensor Networks

Industrial wireless sensor networks (IWSNs) are the fundamental components in the next-generation factories. Due to massive heterogeneous data generated from large-scale IWSNs, it is still challenging to achieve predictable, deterministic, and real-time transmission scheduling. In this article, a framework of priority-aware packet transmission scheduling (PPTS) in cluster-based IWSNs is proposed, where the PPTS strategy, the optimization theory, and the implementation design are systematically considered. In particular, the proposed PPTS strategy not only minimizes the transmission delay of high priority packets but also greatly improves the transmission delay of low priority packets. The optimization theory for end-to-end priority-aware scheduling in cluster-based IWSNs is formalized, which contributes to the optimal solution for multidimensional network resources allocation and achieves the minimum of average transmission delay. Finally, the advantages of the PPTS framework over some existing solutions are demonstrated by a case study.

Compact circularly polarized metaresonator‐enabled deca‐band antenna

AbstractIn this article, a circularly polarized small‐sized deca‐band monopole antenna is proposed and investigated. The proposed antenna consists of gun‐shaped monopole radiator and split‐ring resonator (SRR) array‐loaded partial ground plane present on the top and bottom sides of the substrate, respectively. The antenna is excited by a microstrip line feed and in order to get varied multiband operation with circular polarization, several unique configurations of SRRs are employed as metaresonators. Using the approach of combining resonances of metaresonators and monopole radiator, dual‐, triple‐, hexa‐, and deca‐band operations can be achieved. The permittivity and permeability of the composite metaresonator structure made of SRRs are extracted to illustrate the working principle of the designed multiband antenna. The proposed multiband antenna covers long‐term evolution, WLAN, WiMAX, bluetooth, satellite digital audio radio system (SDARS), radio altimeter, and satellite communication C‐band applications, on a single multifunctional device, much needed in the fast‐growing wireless industry. The antenna is fabricated on a 40 × 47 × 1.5748 mm3 RT Duroid 5880 substrate, and simulations were carried out with the help of the tool Ansys HFSS. The simulated and measured results are in good agreement.

Fusion of Software Defined Networking, Edge Computing, and Blockchain Technology for Wireless Network Virtualization

Wireless network virtualization is regarded as a technology to enable sharing of physical wireless infrastructure and RF slices for improving not only wireless network capacity and coverage but also wireless security. This article provides a perspective of fusion of three emerging technologies: SDN, EC, and blockchain technology for wireless network virtualization. SDN, with the help of controllers, allows dynamic configuration of network resources for their efficient management. EC not only helps to process user signals and queries at respective base stations with the shortest possible delay, but also helps to avoid the need of a high-speed backhaul link between a base station and centralized controllers. Blockchain technology protects owners of wireless infrastructures from a double spending attack that allocates the same wireless resource (RF slice) to multiple virtual wireless networks. The proposed approach aims to reduce business friction and increase the trust and transparency in the wireless networking industry.

Evaluating the Suitability of IEEE 802.11ah for Low-Latency Time-Critical Control Loops

A number of industrial wireless technologies have emerged over the last decade, promising to replace the need for wires in a variety of use cases. Except for customized time division multiple access (TDMA)-based wireless technologies that can achieve ultralow latency over a very limited area, wireless communication generally has reliability and latency issues when it comes to industrial applications. Closed loop communication requires high reliability (over 99%), limited jitter and latency, which poses a challenge especially over a wide area measuring in hundreds of meters. Extended coverage is promised with the advent of sub-GHz technologies, one of them being IEEE 802.11ah which is the only one that offers sufficient data rate for frequent bidirectional communication. Thus, we evaluated IEEE 802.11ah for low-latency time-critical control loops. We propose the network setup for adjusting the network dynamics to that of control loops, enabling limited jitter and high reliability. We explore the scalability of IEEE 802.11ah network hosting both control loops and monitoring sensors that periodically transmit measurements. Assigning the control loop end-nodes to dedicated restricted access window (RAW) slot results in over 99.99% successful deliveries. Furthermore, interpacket delay is concentrated around the cycle-time in the following or preceding beacon interval in case the beacon interval is at least half the value of the shortest cycle-time. Adjusting the beacon interval to the fastest control loop in the network ensures latency requirements at the cost of maximum achievable throughput and energy consumption.

A Distributed Position-Based Routing Algorithm in 3-D Wireless Industrial Internet of Things

Smart factory is a typical application scene of Internet of Things and wireless terminal devices naturally compose a three-dimensional (3-D) industrial wireless network. A primary requirement in the network is delivering packets from source node to destination node. Most geographic routing algorithms are designed for planar networks and they do not suit 3-D networks. In this paper, we extend a greedy perimeter stateless routing algorithm (GPSR) into three dimensions named GPSR-3D. In GPSR-3D, each node decides next hop of a packet by cooperating with only local neighbors and hence this algorithm is totally distributed. GPSR-3D comprises two packet forwarding patterns named greedy forwarding pattern (GFP) and surface forwarding pattern (SFP). In GFP, a node always sends the packet to a neighbor closest to destination and when it fails, SFP is employed for recovery. In SFP, we first divide the whole network space into a set of subspaces based on a novel 3-D geometric structure. Then, a parallel polyhedron traverse algorithm is proposed to recover local minima. A flowchart of GPSR-3D is given to clearly present the process of delivering a packet based on GFP and SFP. Simulation results show that GPSR-3D is of great reliability, energy efficiency and storage efficiency. Specifically, data transmission amount in GPSR-3D is about 67% and 71% to that of multihop Delaunay triangulation (MDT) and GDSTR-3D on average. Moreover, GPSR-3D performs much better than MDT and GDSTR-3D in terms of average storage cost and the average storage space in GPSR-3D is about 48% and 26% to that of MDT and GDSTR-3D, respectively.

Intelligent Latency-Aware Virtual Network Embedding for Industrial Wireless Networks

The growing popularity of industrial wireless networks (IWNs) is driven by various applications with stringent timeliness requests. However, the ossification, deep-rooted in the one-application one-network architecture of traditional IWNs, impedes the evolution of IWNs toward smart factory. As a solution, the slice-based network virtualization (NV) breaks the tight coupling between applications and network infrastructure, and thus provides a more flexible and scalable IWN architecture. The application of NV relies on the algorithms that instantiate multiple virtual networks (VNs) on a substrate infrastructure, known as VN embedding (VNE). However, existing VNE algorithms are not necessarily optimal for IWNs due to the absence of QoS-compliant capacity. To this end, so called iVNE, an intelligent latency-aware VNE scheme, is proposed to provide deadline guarantee for various industrial VNs (IVNs), which involves both static embedding and dynamic forwarding. In the static stage, an anypath embedding algorithm is introduced for the new arrival of IVNs so that their resource demands and deadlines can be satisfied with coarse grain. Then, a dynamic anypath forwarding method is incorporated into iVNE to offer intelligent latency sensing via deep ${Q}$ -learning, and thus forwarding adjustments can be made timely to address the dynamic changes of link quality and network workload. The simulation results are provided to demonstrate the learning efficiency as well as the ability of load-balancing through responsive forwarding under dynamic environment.

Wireless Sensor Network and Industrial Internet of Things Based Industrial Machinery Control and Noise Detector

This paper describes a wireless sensor network and industrial internet of things based Industry machinery control and noise detector, where the using control platform is Arduino, While TCP and IOT is serving as a communication protocol. The function of Arduino is to understand data destination along with the functioning of data to that machine similarly sensors used to take information at their level and fed back for the proper functioning. This paper aims in designing a convenient wireless industry where cabling is not possible. It also has lower installation and maintenance charge for flexible Industry. This paper presents the measurement and reduction of noise from the machines for the betterment of workers.

Latency and Lifetime Enhancements in Industrial Wireless Sensor Networks: A Q-Learning Approach for Graph Routing

Industrial wireless sensor networks usually have a centralized management approach, where a device known as network manager is responsible for the overall configuration, definition of routes, and allocation of communication resources. Graph routing is used to increase the reliability of communication through path redundancy. Some of the state-of-the-art graph-routing algorithms use weighted cost equations to define preferences on how the routes are constructed. The characteristics and requirements of these networks complicate to find a proper set of weight values to enhance network performance. Reinforcement learning can be useful to adjust these weights according to the current operating conditions of the network. In this article, we present the Q-learning reliable routing with a weighting agent approach, where an agent adjusts the weights of a state-of-the-art graph-routing algorithm. The states of the agent represent sets of weights, and the actions change the weights during network operation. Rewards are given to the agent when the average network latency decreases or the expected network lifetime increases. Simulations were conducted on a WirelessHART simulator considering industrial monitoring applications with random topologies. Results show, in most cases, a reduction of the average network latency while the expected network lifetime and the communication reliability are at least as good as what is obtained by the state-of-the-art graph-routing algorithms.

TMSRS: trust management-based secure routing scheme in industrial wireless sensor network with fog computing

Based on fog computer, an industrial wireless sensor network (F-IWSN) is a novel wireless sensor network in the industry. It not only can more efficiently reduce information transmission latency, but also can more beneficially achieve the real-time control and the rapid resource scheduling. However, similar to other distributed networks, it also faces enormous security challenges, especially those internal attacks. The differences from those traditional security schemes are that, one is the trade-off between security, transmission performance and energy consumption to meet the requirements of information convergence and control, the other constructs a multi-dimensional selective forwarding scheme to achieve the real time transmission. In this paper, we propose a Gaussian distribution-based comprehensive trust management system (GDTMS) for F-IWSN. Furthermore, in its trust decision, the grey decision making is introduced to achieve the trade-off between security, transmission performance and energy consumption. The proposed trade-off can effectively select the secure and robust relay node, namely, a trust management-based secure routing scheme. In addition, the proposed schemes are also applicable to defending against bad mouthing attacks. Simulation results show that, the comprehensive performance of GDTMS is better than other similar algorithms. It can effectively prevent the appearance of network holes, and balance the network load, promote the survivability of the network.

Load Balancing for Reliable Self-Organizing Industrial IoT Networks

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.

Lightweight and Physically Secure Anonymous Mutual Authentication Protocol for Real-Time Data Access in Industrial Wireless Sensor Networks

Industrial wireless sensor network (IWSN) is an emerging class of a generalized WSN having constraints of energy consumption, coverage, connectivity, and security. However, security and privacy is one of the major challenges in IWSN as the nodes are connected to Internet and usually located in an unattended environment with minimum human interventions. In IWSN, there is a fundamental requirement for a user to access the real-time information directly from the designated sensor nodes. This task demands to have a user authentication protocol. To satisfy this requirement, this paper proposes a lightweight and privacy-preserving mutual user authentication protocol in which only the user with a trusted device has the right to access the IWSN. Therefore, in the proposed scheme, we considered the physical layer security of the sensor nodes. We show that the proposed scheme ensures security even if a sensor node is captured by an adversary. The proposed protocol uses the lightweight cryptographic primitives, such as one way cryptographic hash function, physically unclonable function, and bitwise exclusive operations. Security and performance analysis shows that the proposed scheme is secure, and is efficient for the resource-constrained sensing devices in IWSN.

Fault-Tolerant Event Region Detection on Trajectory Pattern Extraction for Industrial Wireless Sensor Networks

Poisonous pollutants produced in chemical, plastics, or nuclear power industry are easy to leak and result in a large-scale hazardous event region. Recently, industrial wireless sensor networks (IWSNs) are intended to provide situational awareness in industry site and thus hold the promise of profiling the event region. However, low-cost nodes in IWSNs are prone to fail due to prolonged exposure to harsh environment. This article targets the detection of hazardous event region for IWSNs with faulty nodes. A fault-tolerant event region detection algorithm named TPE-FTED is proposed to formulate faulty nodes identification as a trajectory pattern extraction problem. Through online learning of probabilistic model, each node characterizes the distribution of sensing values under different sensing states. A specific set of probabilistic models can be formed as a trajectory which indicates something special happens. Based on the implicit knowledge from generated trajectories, TPE-FTED conducts pattern matching and checks spatiotemporal constraint to identify the declaration of faulty nodes. Simulation results demonstrate that TPE-FTED achieves low false alarm rate as well as high detection accuracy.

Industrial wireless sensor and actuator networks in industry 4.0: Exploring requirements, protocols, and challenges—A MAC survey

SummaryThe vision to connect everyday physical objects to the Internet promises to create the Internet of Things (IoT), which is expected to integrate the diverse technologies such as sensors, actuators, radio frequency identification, communication technologies, and Internet protocols. Thus, IoT promises to transfer traditional industry to advance digital industry known as the Industry 4.0.At the core of the Industry 4.0 are the wireless sensor networks (WSNs) and wireless sensor and actuator networks (WSANs) that led to the development of industrial wireless sensor networks (IWSNs) and industrial wireless sensor and actuator networks (IWSANs). These networks play a central role of connecting machines, parts, products, and humans and create a diverse set of new applications to support intelligent and autonomous decision making.The IWSAN is a promising technology for numerous industrial applications because of their several potential benefits such as simple deployment, low cost, less complexity, and mobility support. However, despite such benefits, they impose several unique challenges at different layers of the protocol stack when deploying them for various monitoring and control applications in the Industry 4.0. In this article, we explore IWSAN, its applications, requirements, challenges, and solutions in the context of industrial control applications. Our main focus is on the medium access control (MAC) layer that can be exploited to satisfy such requirements. Our discussion presents extensive background study of the MAC schemes and it reviews the MAC protocols of the existing wireless standards and technologies. A number of application‐specific MAC protocols developed to support industrial applications, which are not part of these standards, are also elaborated. We rationalize to what extent the existing standards and protocols help in solving such requirements as laid down by the Industry 4.0. In the end, we emphasize on existing challenges and present important future directions.

Uplink Low-Power Scheduling for Delay-Bounded Industrial Wireless Networks Based on Imperfect Power-Domain NOMA

The power-domain non-orthogonal multiple access (NOMA) supports multiple packet reception, which can be leveraged for delay-bounded applications in industrial wireless networks (IWNs). However, it suffers from high power consumption on transmitters, which poses challenges for battery-powered wireless sensors. Given the delay bound for NOMA-based IWNs, the problem of minimizing aggregate power consumption of transmitters is therefore of great value. In a previous paper, we have addressed the problem under the model of perfect $k$ -successive interference cancellation ( $k$ -SIC). In this paper, we study the same problem, however, under the model of imperfect $k$ -SIC, which is more general in theory and more realistic in practice. For the existence of the optimal solution, we first present an explicit sufficient and necessary condition, which correlates three key parameters of network system together. We also propose a polynomial-time optimal algorithm with complexity $O(n^2)$ . We further consider the same problem with discrete transmit powers, and present an approximation algorithm with complexity $O(n^2)$ . Performance evaluation reveals that the delay bound requirement has tremendous impacts on both the aggregate power consumption and the maximum transmit power. Relative to the perfect SIC, the residual error caused by imperfect SIC results in extra power consumption of transmitters. However, the extra power consumption is gradually diminished with the further relaxation of the delay bound.

Measurement and Characterization of Electromagnetic Noise in Edge Computing Networks for the Industrial Internet of Things.

Edge computing and the Internet of Things (IOT) provide the technological basis for the development of intelligent manufacturing nowadays. In order to support the intelligent interconnection and application of all kinds of equipment in the industrial field, edge computing should be equipped close to or embedded in all kinds of equipment nodes in the industrial wireless network. Therefore, it is meaningful to investigate the wireless network design of the Industrial Internet of Things. Low power wireless sensor devices are widely used in the Industrial Internet of Things (IIoT), which are sensitive to electromagnetic noise. The electromagnetic noises in industrial scenarios are significantly different from the conventional assumed white noise. In this paper, the measurement results of electromagnetic noises at three different test positions are given in an automobile factory. The spectrum occupancy of the factory wireless environment in the 300 MHz–3 GHz band was obtained by frequency domain measurement. In the time domain measurement, four statistical parameters of the three bands of 315 MHz, 433 MHz, and 916 MHz were measured, and the electromagnetic noise distributions in different plant areas and different frequency bands were analyzed. According to the measurement results, the time-varying characteristics of electromagnetic noise can be characterized by continuous hidden Markov models (CHMM). These results are informative to the design and optimization for the edge computing networks for IIoT.

Histogram partitioning algorithms for adaptive and autonomous threshold estimation in cognitive radio–based industrial wireless sensor networks

AbstractModern energy detectors typically use adaptive threshold estimation algorithms to improve signal detection in cognitive radio–based industrial wireless sensor networks (CR‐IWSNs). However, a number of adaptive threshold estimation algorithms often perform poorly under noise uncertainty conditions since they are typically unable to auto‐adapt their parameter values per changing spectra conditions. Consequently, in this paper, we have developed two new algorithms to accurately and autonomously estimate threshold values in CR‐IWSNs under dynamic spectra conditions. The first algorithm is a parametric‐based technique termed the histogram partitioning algorithm, whereas the second algorithm is a fully autonomous variant termed the mean‐based histogram partitioning algorithm. We have evaluated and compared both algorithms with some well‐known methods under different CR sensing conditions. Our findings indicate that both algorithms maintained over 90% probability of detection in both narrow and wideband sensing conditions and less than 10% probability of false alarm under noise‐only conditions. Both algorithms are quick and highly scalable with a time complexity of O(V), where V is the total number of input samples. The simplicity, effectiveness, and viability of both algorithms make them typically suited for use in CR‐IWSN applications.

A spanning tree construction algorithm for industrial wireless sensor networks based on quantum artificial bee colony

In industrial Internet, many intelligent applications are implemented based on data collection and distribution. Data collection and data distribution in the wireless sensor networks are very important, where the node topology can be described by the spanning tree for obtaining an efficient transmission. Classical algorithms in graph theory such as the Kruskal algorithm or Prim algorithm can only find the minimum spanning tree (MST) in industrial wireless sensor networks. Swarm intelligence algorithm can obtain multiple solutions in one calculation. Multiple solutions are very helpful for improving the reliability of industrial wireless sensor networks.In this paper, we combine quantum computing with artificial bee colony and design a spanning tree construction algorithm for industrial wireless sensor networks. Quantum computations are introduced into the onlooker bees search. Food source replacement strategy is improved. Finally, the algorithm is simulated and evaluated. The results show that the new proposed algorithm can obtain more alternative solutions and has a better performance in search efficiency.