Wireless Sensor-actuator Networks Research Articles

MERA: Meta-Learning Based Runtime Adaptation for Industrial Wireless Sensor-Actuator Networks

IEEE 802.15.4-based industrial wireless sensor-actuator networks (WSANs) have been widely deployed to connect sensors, actuators, and controllers in industrial facilities. Configuring an industrial WSAN to meet the application-specified quality of service (QoS) requirements is a complex process, which involves theoretical computation, simulation, and field testing, among other tasks. Since industrial wireless networks become increasingly hierarchical, heterogeneous, and complex, many research efforts have been made to apply wireless simulations and advanced machine learning techniques for network configuration. Unfortunately, our study shows that the network configuration model generated by the state-of-the-art method decays quickly over time. To address this issue, we develop a ME ta-learning based R untime A daptation (MERA) method that efficiently adapts network configuration models for industrial WSANs at runtime. Under MERA, the parameters of the network configuration model are explicitly trained such that a small number of optimization steps with only a few new measurements will produce good generalization performance after the network condition changes. We also develop a data sampling method to reduce the measurements required by MERA at runtime without sacrificing its performance. Experimental results show that MERA achieves higher prediction accuracy with less physical measurements, less computation time, and longer adaptation intervals compared to a state-of-the-art baseline.

Online Distributed Schedule Randomization to Mitigate Timing Attacks in Industrial Control Systems

Industrial control systems (ICSs) consist of a large number of control applications that are associated with periodic real-time flows with hard deadlines. To facilitate large-scale integration, remote control, and co-ordination, wireless sensor and actuator networks form the main communication framework in most ICSs. Among the existing wireless sensor and actuator network protocols, WirelessHART is the most suitable protocol for real-time applications in ICSs. The communications in a WirelessHART network are time-division multiple access based. To satisfy the hard deadlines of the real-time flows, the schedule in a WirelessHART network is pre-computed. The same schedule is repeated over every hyperperiod (i.e., lowest common multiple of the periods of the flows). However, a malicious attacker can exploit the repetitive behavior of the flow schedules to launch timing attacks (e.g., selective jamming attacks). To mitigate timing attacks, we propose an online distributed schedule randomization strategy that randomizes the time-slots in the schedules at each network device without violating the flow deadlines, while ensuring the closed-loop control stability. To increase the extent of randomization in the schedules further, and to reduce the energy consumption of the system, we incorporate a period adaptation strategy that adjusts the transmission periods of the flows depending on the stability of the control loops at runtime. We use Kullback-Leibler divergence and prediction probability of slots as two metrics to evaluate the performance of our proposed strategy. We compare our strategy with an offline centralized schedule randomization strategy. Experimental results show that the schedules generated by our strategy are 10% to 15% more diverse and 5% to 10% less predictable on average compared to the offline strategy when the number of base schedules and keys vary between 4 and 6 and 12 and 32, respectively, under all slot utilization (number of occupied slots in a hyperperiod). On incorporating period adaptation, the divergence in the schedules reduceat each period increase with 46% less power consumption on average.

Revealing Smart Selective Jamming Attacks in WirelessHART Networks

As a leading industrial wireless standard, WirelessHART has been widely implemented to build wireless sensor-actuator networks (WSANs) in industrial facilities, such as oil refineries, chemical plants, and factories. For instance, 54,835 WSANs that implement the WirelessHART standard have been deployed globally by Emerson process management, a WirelessHART network supplier, to support process automation. While the existing research to improve industrial WSANs focuses mainly on enhancing network performance, the security aspects have not been given enough attention. We have identified a new threat to WirelessHART networks, namely smart selective jamming attacks, where the attacker first cracks the channel usage, routes, and parameter configuration of the victim network and then jams the transmissions of interest on their specific communication channels in their specific time slots, which makes the attacks energy efficient and hardly detectable. In this paper, we present this severe, stealthy threat by demonstrating the step-by-step attack process on a 50-node network that runs a publicly accessible WirelessHART implementation. Experimental results show that the smart selective jamming attacks significantly reduce the network reliability without triggering network updates.

Autonomous Traffic-Aware Scheduling for Industrial Wireless Sensor-Actuator Networks

Recent years have witnessed rapid adoption of low-power Wireless Sensor-Actuator Networks (WSANs) in process industries. To meet the critical demand for reliable and real-time communication in harsh industrial environments, the industrial WSAN standards make a set of specific design choices, such as employing the Time-Slotted Channel Hopping (TSCH) technique. Such design choices distinguish industrial WSANs from traditional Wireless Sensor Networks, which were designed for best-effort services. Recently, there has been increasing interest in developing new methods to enable autonomous transmission scheduling for industrial WSANs that run TSCH and the Routing Protocol for Low-Power and Lossy Networks (RPL). Our study shows that the current approaches fail to consider the traffic loads of different devices when assigning time slots and channels, which significantly compromises network performance when facing high data rates. In this article, we introduce a novel Autonomous Traffic-Aware transmission scheduling method for industrial WSANs. The device that runs ATRIA can detect its traffic load based on its local routing information and then schedule its transmissions accordingly without the need to exchange information with neighboring devices. Experimental results show that ATRIA provides significantly higher end-to-end network reliability and lower end-to-end latency without introducing additional overhead compared with a state-of-the-art baseline.

AdaptiveHART: An Adaptive Real-Time MAC Protocol for Industrial Internet-of-Things

Wireless sensor–actuator networks (WSAN) for real-time reliable communications are being embraced in the Industrial Internet of Things. One key property required for WSAN is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adaptability</i> with respect to dynamic environments. Most existing studies assume that a network manager computes global schedules and disseminates schedule information to every node whenever the network parameters need to be updated. Such a centralized approach may degrade control performance due to nonreal-time response to dynamic environments. In this article, we introduce a novel time division multiple access MAC protocol, AdaptiveHART, which updates the network parameters in real-time without the dissemination intervals. AdaptiveHART achieves a reduction in adaptation latency up to 74%, maximum schedulable ratio, and control performance up to 75% than the conventional WirelessHART. We assess our protocol using a stochastic response time analysis, which provides an accurate end-to-end delay distribution and a schedulability condition that can guarantee real-time performance in WSAN.

Assisted Navigation Algorithm for Wireless Sensor Actuator and Robot Networks

Wireless Sensor, Actuator and Robot Networks (WSARNs) are made of mobile and static sensor nodes that interact in order to collaboratively perform specific tasks, such as supporting assisted navigation for mobile robotic nodes that carry out requested operations in hostile environments, where the human presence is impracticable. In this regard, it is worth noting that assisted navigation algorithms have a highly dynamic nature, and are implemented by sensor nodes that are characterized by limited transmission power and lean autonomy in terms of computing and memory capacity. This paper presents an improved version of the assisted navigation algorithm based on the concept of “credit field”. The main aim of the proposed algorithm is to reduce and balance the energy consumption among the static sensor nodes when running the algorithm to manage the presence of obstacles and adversary areas, thus extending the lifetime of WSARNs. The algorithm has been tested on a hybrid sensor network that employs Mica2 Motes as static sensor nodes and Lego Mindstorms robots integrated with a Stargate board developed by Crossbow as mobile nodes.

Wireless fieldbus networking with precision time synchronization for a low-power WSAN

A wireless sensor actuator network (WSAN) is an essential part of the industrial Internet of things (IIoT) with a cyber-physical system (CPS). However, the lack of time synchronization support for WSANs to date means that losses in synchronization accuracy have not been overcome. In this manuscript, we design a real-time kernel to resolve the precision time synchronization (PTS) problem and achieve dynamic automatic synthesis and rapid deployment in a complex WSAN system. Furthermore, tight coupling between wireless control and time synchronization motivates a Modbus-based precision time protocol (PTP) codesign that integrates industrial fieldbus networks and a PTS design. The experimental results indicate that our proposed PTP performance can far exceed the time synchronization requirement of an industrial real-time system. Finally, the proposed solution is successfully applied to an IoT-based smart lighting system.

A Controller Switching Mechanism for Resilient Wireless Sensor–Actuator Networks

Controller failures can result in unsafe physical plant operations and deteriorated performance in industrial cyber–physical systems. In this paper, we present a controller switching mechanism over wireless sensor–actuator networks to enhance the resiliency of control systems against problems and potential physical failures. The proposed mechanism detects controller failures and quickly switches to the backup controller to ensure the stability of the control system in case the primary controller fails. To show the efficacy of our proposed method, we conduct a performance evaluation using a hardware-in-the-loop testbed that considers both the actual wireless network protocol and the simulated physical system. Results demonstrate that the proposed scheme recovers quickly by switching to a backup controller in the case of controller failure.

Design and Performance Analysis of Hybrid Energy Harvesting and WSN Application for More Life Time and High Throughput

the technology of wireless sensor-actuator networks (WSANs) is widely employed in the applications of IoT due to its wireless nature and it does not involve any wired structure. The wireless systems that are battery-driven can easily reconfigure the existing devices and sensors efficiently in the manufacturing units without employing any cable for power operation as well as for communication. The wireless sensor-actuator networks that are based on IEEE 802.15.4 consumes significantly less power. These networks are designed and built cost-effectively by considering the capacity of battery and expense so that they can be employed for many applications. The application of a typical wireless Autonomous Scheduling and Distributed Graph Routing (DDSR) has illustrated the reliability of employing its basic approaches for almost ten years and it consists of the accurate plot for routing and time-slotted channel hopping therefore ensuring accurate low-power wireless communication in the processing site. Officially declared by the controversial statements associated with the government of Greek experiences fourth industrialization. There is a huge requirement for sensor nodes link via WSAN in the industrial site. Also, reduced computational complexity is one of the drawbacks faced by the existing standards of WSAN which is caused because of their highly centralized traffic management systems and thereby significantly improves the consistency and accessibility of network operations at the expense of optimization. This research work enables the study of efficient Wireless DGR network management and also introduces an alternative for DDSR by enabling the sensor nodes to determine their data traffic routes for the transmission of data. When compared to the above two physical routing protocols, the proposed technique can drastically improve the performance of a network, throughput, and energy consumption under various aspects. Energy harvesting (EH) plays a significant role in the implementation of large IoT devices. The requirement for subsequent employment of power sources is eliminated by The efficient approach of Energy Harvesting and thereby providing a relatively close- perpetual working environment for the network. The structural concept of routing protocols that are designed for the IoT applications which are based on the wireless sensor has been transformed into "energy-harvesting-aware" from the concept of "energy-aware" because of the development in the Energy harvesting techniques. The main objective of the research work is to propose a routing protocol that is energy-harvesting-aware for the various network of IoT in case of acoustic sources of energy. A novel algorithm for routing called Autonomous Scheduling and Distributed Graph Routing (DDSR) has been developed and significantly improved by incorporating a new “energy back-off” factor. The proposed algorithm when integrated with various techniques of energy harvesting enhances the longevity of nodes, quality of service of a network under increased differential traffic, and factors influencing the accessibility of energy. The research work analyses the performance of the system for various constraints of energy harvesting. When compared to previous routing protocols the proposed algorithm achieves very good energy efficiency in the network of distributed IoT by fulfilling the requirements of QoS.

Wireless Sensor Actuator Network Architecture and Energy Model of a Camera Based Lighting Management System

Communication protocols and wireless networking technique is a cohesive part of any light management system. IEEE 802.15.4 standard based networking techniques for the climate-adaptive light management system and its energy model for sensor actuator node is the focus of this paper. This light integrated scheme with adaptive controls provides the desired illuminance at appropriate times with uniformity, by reducing the discomfort glare and energy use. The first part of this paper investigates the architecture and energy consumption of camera-based wireless sensor-actuator nodes with the help of energy models, including a control unit for the Light Management System. Then focused on the energy savings and techno-economic analysis of this wireless networked lighting system in a test room with automated control of Light Emitting Diode luminaire and Venetian blinds. The wireless sensor actuator networked lighting system performance is analyzed by evaluating the node energy consumption in idle and active mode with real time measurements. The energy consumption evaluation of the nodes allows users to improve node life time and think about power management schemes. The climate-adaptive control scheme shows improved uniformity and significant energy savings.

Enabling Cross-technology Communication from LoRa to ZigBee in the 2.4 GHz Band

IEEE 802.15.4-based wireless sensor-actuator networks have been widely adopted by process industries in recent years because of their significant role in improving industrial efficiency and reducing operating costs. Today, industrial wireless sensor-actuator networks are becoming tremendously larger and more complex than before. However, a large, complex mesh network is hard to manage and inelastic to change once the network is deployed. In addition, flooding-based time synchronization and information dissemination introduce significant communication overhead to the network. More importantly, the deliveries of urgent and critical information such as emergency alarms suffer long delays, because those messages must go through the hop-by-hop transport. A promising solution to overcome those limitations is to enable the direct messaging from a long-range radio to an IEEE 802.15.4 radio. Then messages can be delivered to all field devices in a single-hop fashion. This article presents our study on enabling the cross-technology communication from LoRa to ZigBee using the energy emission of the LoRa radio as the carrier to deliver information. Experimental results show that our cross-technology communication approach provides reliable communication from LoRa to ZigBee with the throughput of up to 576.80 bps and the bit error rate of up to 5.23% in the 2.4 GHz band.

Communication system improvement with control performance based on link quality in wireless sensor actuator networks

&lt;span lang="EN-US"&gt;New communication and networking paradigms started with wireless sensor actuator networks (WSANs) to introduce new applications. One of these is the automatic gain control system (AGC). It will enable a high degree of the decentralized and mobile control. In this study, neural networks (NN) with fuzzy logic (one of the techniques of artificial intelligence (AI)) is used to enhance the control performance depending on the link quality. The NN and fuzzy inference system (FIS) with Mamdani’s method used to build a model reference, adaptive controller, for recompensing for delay time packets losses, and improving the reliability of WSAN. Between 88.62% and 99.99%, validation data is obtained for the medium and high conditions of operation with the proposed algorithm. Experimental and simulation results show a promising approach.&lt;/span&gt;

Centralized fusion estimation over wireless sensor-actuator networks with unobservable packet dropouts

This paper studies centralized fusion estimation over a wireless sensor-actuator network, where packet dropouts cannot be observed by the fusion estimator. For such a system, we obtain an optimal linear fused estimation of system states, also known as optimal linear estimator. Then, we establish a necessary and sufficient condition for the stability of the optimal linear estimator. Finally, we show that the estimation performance is monotonically decreasing with respect to the observation packet-arrival rate. By analyzing a sequence that converges to the covariance of the optimal linear estimator, an analytical relationship between the estimation performance and the control packet-arrival rate is obtained. Simulation examples are given to illustrate the main results.

VES: A Mixed-Reality Development Platform of Navigation Systems for Blind and Visually Impaired.

Herein, we describe the Virtually Enhanced Senses (VES) system, a novel and highly configurable wireless sensor-actuator network conceived as a development and test-bench platform of navigation systems adapted for blind and visually impaired people. It allows to immerse its users into “walkable” purely virtual or mixed environments with simulated sensors and validate navigation system designs prior to prototype development. The haptic, acoustic, and proprioceptive feedback supports state-of-art sensory substitution devices (SSD). In this regard, three SSD were integrated in VES as examples, including the well-known “The vOICe”. Additionally, the data throughput, latency and packet loss of the wireless communication can be controlled to observe its impact in the provided spatial knowledge and resulting mobility and orientation performance. Finally, the system has been validated by testing a combination of two previous visual-acoustic and visual-haptic sensory substitution schemas with 23 normal-sighted subjects. The recorded data includes the output of a “gaze-tracking” utility adapted for SSD.

On a multisensor knowledge fusion heuristic for the Internet of Things

Internet of Things (IoT) is envisioned as the interconnection of the Internet with sensing and actuating devices. IoT systems are usually designed to collect massive amounts of data from multiple and possibly conflicting sources. Nevertheless, data must be refined before being stored in a repository, so as information can be correctly extracted for further uses. Knowledge fusion is an important technique to identify and eliminate erroneous data from compromised sources or any mistakes that might have occurred during the extraction process. We propose a new multisensor knowledge fusion heuristic (MKFH) for IoT supporting the knowledge extraction and transfer needed to further knowledge management, also discuss the role of reinforcement learning over integration on a multi-application wireless sensor/actuator network (WSAN). Results shows that the proposed multisensor knowledge fusion heuristic is compatible with the IoT paradigm and enhances integration.

Coordination schemes for resource oriented operation in wireless sensor actuator networks with queuing theory

Wireless sensor and actuator networks provide better servicing in automation process. The best effort service of wireless sensor node has to mitigate the scenario of appropriate response of actuation from actuator. The proposed work focuses on wireless sensor actuator network based cost estimation (WSANCE) where two objectives of sensed data and actuator response is been considered. The first scenario work states that minimization of resource such as energy and waiting time of events with single mobile actuator in a sensing terrain. The second scenario work states that maximizing the data acquisition with two actuators moving in a sensing terrain with controlled mobility. The total cost is calculated in both the scenarios as a sum of service and waiting cost associated with the sensor actuator resources. Simulation result with networking availability has been calculated with success rate and latency.

Optimal scheduling for maximizing information freshness and system performance in industrial cyber–physical systems

“Age of Information” is a newly introduced metric, getting vivid attention for measuring the freshness of information in real-time networks. This parameter has evolved to guarantee the timely reception of information from the latest status update received by a user from any real-time application. In this paper, we study a centralized, closed-loop, networked controlled industrial wireless sensor–actuator network for cyber–physical production systems. Here, we jointly address the problem of transmission scheduling of sensor updates and the restoration of an information flow-line after any real-time update, having hard-deadline, drops from it, resulting in a break in the loop. Unlike existing real-time scheduling policies that only ensure timely updates, this work aims to accomplish both the time-sensitivity and data freshness in new and regenerative real-time updates in terms of the ‘age’ of information. Here, the coexistence of both cyber and physical units and their individual requirements for providing the quality of service to the system, as a whole, seems to be one of the major challenges to handle. In this work, minimization of staleness of the time-critical updates to extract maximum utilization out of its information content and its effects on other network performances are thoroughly investigated. A greedy scheduling policy called “Deadline-aware Highest Latency First” has been used to solve this problem; its performance optimality is proved analytically. Finally, our claim is validated by comparing the results obtained by our algorithm with those of other popular scheduling policies through extensive simulations.

A schedule randomization policy to mitigate timing attacks in WirelessHART networks

Industrial control systems consist of large-scale wireless sensor-actuator networks (WSAN) that control the physical plant. The communications between the sensors and the actuators need to be reliable and guaranteed within strict deadlines for safe operation of all the system components in industrial setups. WirelessHART is the most suitable and widely adopted WSAN standard that serves as the medium of communication in industries. To satisfy deadlines of real-time flows in WirelessHART networks, the centralized network manager decides the communication schedule during network initialization. The same schedule repeats every hyperperiod. The repetitive nature of the communication slots over every hyperperiod makes the system vulnerable to timing attacks which can eventually disrupt the safety of the system. To mitigate such attacks, we propose SlotSwapper, a moving target defense mechanism that randomizes the communication slots over a hyperperiod schedule without violating the feasibility constraints of real-time flows in WirelessHART networks. We show that SlotSwapper is optimal for single-channel WirelessHART network with real-time harmonic flows. We extensively evaluated our algorithm with $$\varvec{4800}$$ flow sets over $$\varvec{100}$$ Tmote sky motes in Cooja simulator. We use Prediction Probability of slots of a schedule to measure the security provided by SlotSwapper. We use Kullback–Leibler divergence to measure the divergence of our solution w.r.t. a truly random solution.

Cracking Channel Hopping Sequences and Graph Routes in Industrial TSCH Networks

Industrial networks typically connect hundreds or thousands of sensors and actuators in industrial facilities, such as manufacturing plants, steel mills, and oil refineries. Although the typical industrial Internet of Things (IoT) applications operate at low data rates, they pose unique challenges because of their critical demands for reliable and real-time communication in harsh industrial environments. IEEE 802.15.4-based wireless sensor-actuator networks (WSANs) technology is appealing for use to construct industrial networks because it does not require wired infrastructure and can be manufactured inexpensively. Battery-powered wireless modules easily and inexpensively retrofit existing sensors and actuators in industrial facilities without running cables for communication and power. To address the stringent real-time and reliability requirements, WSANs made a set of unique design choices such as employing the Time-Synchronized Channel Hopping (TSCH) technology. These designs distinguish WSANs from traditional wireless sensor networks (WSNs) that require only best effort services. The function-based channel hopping used in TSCH simplifies the network operations at the cost of security. Our study shows that an attacker can reverse engineer the channel hopping sequences and graph routes by silently observing the transmission activities and put the network in danger of selective jamming attacks. The cracked knowledge on the channel hopping sequences and graph routes is an important prerequisite for launching selective jamming attacks to TSCH networks. To our knowledge, this article represents the first systematic study that investigates the security vulnerability of TSCH channel hopping and graph routing under realistic settings. In this article, we demonstrate the cracking process, present two case studies using publicly accessible implementations (developed for Orchestra and WirelessHART), and provide a set of insights.

Parameter Self-Adaptation for Industrial Wireless Sensor-Actuator Networks

Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption by industrial Internet of Things applications in recent years. A WSAN typically connects sensors, actuators, and controllers in industrial facilities, such as steel mills, oil refineries, chemical plants, and infrastructures implementing complex monitoring and control processes. IEEE 802.15.4–based WSANs operate at low power and can be manufactured inexpensively, which makes them ideal where battery lifetime and costs are important. Recent studies have shown that the selection of network parameters has a significant effect on network performance. However, the current practice of parameter selection is largely based on experience and rules of thumb involving a coarse-grained analysis of expected network load and dynamics or measurements during a few field trials, resulting in non-optimal decisions in many cases. In this work, we develop P-SAFE (Parameter Selection and Adaptation FramEwork), which optimally selects the network parameters based on the application quality-of-service demands and adapts the parameter configuration at runtime to consistently satisfy the dynamic requirements. We implement P-SAFE and evaluate it on three physical testbeds. Experimental results show that our solution can significantly better meet the application quality-of-service demand compared to the state of the art.