Wireless Sensor-actuator Networks Research Articles

Efficient Holistic Control

Industrial automation is embracing wireless sensor-actuator networks (WSANs). Despite the success of WSANs for monitoring applications, feedback control poses significant challenges due to data loss and stringent energy constraints in WSANs. Holistic control adopts a cyber-physical system approach to overcome the challenges by orchestrating network reconfiguration and process control at run time. Fundamentally, it leverages self-awareness across control and wireless boundaries to enhance the resiliency of wireless control systems. In this article, we explore efficient holistic control designs to maintain control performance while reducing the communication cost. The contributions of this work are five-fold: (1) We introduce a holistic control architecture that integrates Low-power Wireless Bus (LWB) and two control strategies, rate adaptation and self-triggered control ; (2) We present heuristics-based and optimal rate selection algorithms for rate adaptation; (3) We design novel network adaptation mechanisms to support rate adaptation and self-triggered control in a multi-hop WSAN; (4) We build WCPS-RT, a real-time network-in-the-loop simulator that integrates MATLAB/Simulink and a physical WSAN testbed to evaluate wireless control systems; (5) We empirically explore the tradeoff between communication cost and control performance in holistic control approaches. Our studies show that rate adaptation and self-triggered control offer advantages in control performance and energy efficiency, respectively, in normal operating conditions. The advantage in energy efficiency of self-triggered control, however, may diminish under harsh physical and wireless conditions due to the cost of recovering from data loss and physical disturbances.

An architecture for resilient intrusion detection in ad-hoc networks

We study efficient and lightweight Intrusion Detection Systems (IDS) for ad-hoc networks via the prism of IPv6-enabled Wireless Sensor Actuator Networks. These networks consist of highly constrained devices able to communicate wirelessly in an ad-hoc fashion, thus following the architecture of ad-hoc networks. Current state-of-the-art (IDS) has been developed taking into consideration the architecture of conventional computer networks, and as such they do not efficiently address the paradigm of ad-hoc networks, that is highly relevant in emergent networks, such as the Internet of Things (IoT). In this context, the network properties of resilience and redundancy have not been studied yet. In this work, we firstly identify a trade-off between the communication overhead and energy consumption of an IDS (as captured by the number of active IDS agents in the network) and the performance of the system in terms of successfully identifying attacks. In order to fine tune this trade-off, we model such networks as Random Geometric Graphs; a rigorous approach that allows us to capture underlying structural properties of the network. We then introduce a novel IDS architectural approach that consists of a central IDS agent a set of distributed IDS agents deployed uniformly at random over the network area. These nodes are able to efficiently detect attacks at the networking layer in a collaborative manner by monitoring locally available network information provided by IoT routing protocols such as RPL. Our detailed experimental evaluation demonstrates significant performance gains in terms of communication overhead and energy consumption while maintaining high detection rates. We also show that the performance of our IDS in ad-hoc networks does not rely on the size of the network but on fundamental underling network properties, such as the network topology and the average degree of the nodes. Conducted experiments show that our proposed IDS architecture is resilient against frequent topology changs due to nodes failures.

Mobile Collector-Based Cost Balancing Scheme for Uniform Data Gathering Delay and Energy Consumption in Wireless Sensor Actuator Networking Systems

The sink hole problem is a critical issue for data collection in wireless sensor networks. Recent research has indicated that the mobility of actuators in wireless sensor actuator networks (WSANs) alleviates the sink hole problem. However, mobile actuator-based data collection may result in unsatisfactory data gathering delay, which is not acceptable for delay-sensitive real time applications. Thus, planning the optimal path for mobile collector is a critical challenge in WSANs to balance between the prolongation of network lifetime and the reduction of the data gathering delay. To address this issue, we propose a mobile collector-based cost balancing algorithm to achieve uniform data gathering delay and energy consumption based on the adaptive region partitioning and dynamic polling point selection. The proposed algorithm uses multiple mobile collectors and partitions the sensing area into several regions that are monitored by the mobile collectors according to the distribution of cost in the area. It also dynamically determines moving trajectory of each mobile collector by selecting the polling points to visit considering the distance to travel and the nodes’ energy consumption. The superiority of the proposed algorithm is validated by theoretical analysis and simulation results.

An Event-based Local Action Paradigm to Improve Energy Efficiency in Queriable Wireless Sensor Actuator Networks

Wireless sensor networks (WSN) are deployed in a multitude of applications both in industrial and academic fields. In recent years, due to the emerge of Internet of Things (IoT) technologies and Vehicle2X communication scenarios, novel challenges for wireless sensor network platforms - regarding hardware and software - arose. Thus, challenges known from big data processing have reached the WSN scope and consequently approaches and methods have been devised to handle these. One such approach is queriable wireless sensor networks which enable their users the specification of sensing tasks in a declarative way without the need to re-program nodes in case the application requirements change. As many current WSN applications feature active parts with which nodes can directly influence their environment, the term wireless sensor actuator networks (WSAN) has been coined, setting such networks apart from solely passively measuring networks.In this article, we will present a short introduction to big data processing in wireless sensor networks which motivates the usage of queriable networks. We will show that in order to enable a WSAN to carry out actions energy-efficiently and in a timely manner, an event-based action model is favorable. Additionally, we will demonstrate how such an event system can be used to improve sub query performance in WSNs. We conclude with an evaluation regarding the benefit of combining this approach with wake-up receiver technologies based on a qualitative energy efficiency definition for WSN.

Towards a next-generation production system for industrial robots: A CPS-based hybrid architecture for smart assembly shop floors with closed-loop dynamic cyber physical interactions

Given the multiple varieties and small batches, the production of industrial robots faces the ongoing challenges of flexibility, self-organization, self-configuration, and other “smart” requirements. Recently, cyber physical systems have provided a promising solution for the requirements mentioned above. Despite recent progress, some critical issues have not been fully addressed at the shop floor level, including dynamic reorganization and reconfiguration, ubiquitous networking, and time constrained computing. Toward the next generation production system for industrial robots, this study proposed a hybrid architecture for smart assembly shop floors with closed-loop dynamic cyber physical interactions. Aiming for dynamic reorganization and reconfiguration, the study also proposed modularized smart assembly units for the deployment of physical assembly processes. Enabling technologies, such as multiagent system (MAS), self-organized wireless sensor actuator networks, and edge computing, were discussed and then integrated into the proposed architecture. Furthermore, a multijoint robot assembly process was selected as a target scenario. Thus, an MAS was developed to simulate the coordination and negotiation mechanisms for the proposed architecture on the basis of the Java Agent Development Framework platform.

Decentralized Event-Triggered Adaptive Control of Discrete-Time Nonzero-Sum Games Over Wireless Sensor-Actuator Networks With Input Constraints.

This article studies an event-triggered communication and adaptive dynamic programming (ADP) co-design control method for the multiplayer nonzero-sum (NZS) games of a class of nonlinear discrete-time wireless sensor-actuator network (WSAN) systems subject to input constraints. By virtue of the ADP algorithm, the critic and actor networks are established to attain the approximate Nash equilibrium point solution in the context of the constrained control mechanism. Simultaneously, as the sensors and actuators are physically distributed, a decentralized event-triggered communication protocol is presented, accompanied by a dead-zone operation which avoids the unnecessary events. By predefining the triggering thresholds and compensation values, a novel adaptive triggering condition is derived to guarantee the stability of the event-based closed-loop control system. Then resorting to the Lyapunov theory, the system states and the critic/actor network weight estimation errors are proven to be ultimately bounded. Moreover, an explicit analysis on the nontriviality of the interevent times is also provided. Finally, two numerical examples are conducted to validate the effectiveness of the proposed method.

Efficient Resource Scheduling for Multipath Retransmission over Industrial WSAN Systems.

With recent adoption of Wireless Sensor-Actuator Networks (WSANs) in industrial automation, wireless control systems have emerged as a frontier of industrial networks. Hence, it has been shown that existing standards and researches concentrate on the reliability and real-time performance of WSANs. The multipath retransmission scheme with multiple channels is a key approach to guarantee the deterministic wireless communication. However, the efficiency of resource scheduling is seldom considered in applications with diverse data sampling rates. In this paper, we propose an efficient resources scheduling algorithm for multipath retransmission in WSANs. The objective of our algorithm is to improve efficiency and schedulability for the use of slot and channel resources. In detail, the proposed algorithm uses the approaches of CCA (clear channel assessment)-Embedded slot and Multiple sinks with Rate Monotonic scheme (CEM-RM) to decrease the number of collisions. We have simulated and implemented our algorithm in hardware and verified its performance in a real industrial environment. The achieved results show that the proposed algorithm significantly improves the schedulability without trading off reliability and real-time performance.

Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks

Wireless sensor-actuator networks (WSANs) technology is appealing for use in the industrial Internet of Things (IoT) applications because it does not require wired infrastructure. Battery-powered wireless modules easily and inexpensively retrofit existing sensors and actuators in the industrial facilities without running cabling for communication and power. The 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. Almost, a decade of real-world deployments of WirelessHART standard has demonstrated the feasibility of using its core techniques including reliable graph routing and time slotted channel hopping (TSCH) to achieve reliable low-power wireless communication in the industrial facilities. Today, we are facing the fourth Industrial Revolution as proclaimed by political statements related to the Industry 4.0 Initiative of the German Government. There exists an emerging demand for deploying a large number of field devices in an industrial facility and connecting them through the WSAN. However, a major limitation of current WSAN standards is their limited scalability due to their centralized routing and scheduling that enhance the predictability and visibility of network operations at the cost of scalability. This paper decentralizes the network management in WirelessHART and presents the first Di stributed ${G}$ raph routing and autonomous ${S}$ cheduling (DiGS) solution that allows the field devices to compute their own graph routes and transmission schedules. The experimental results from two physical testbeds and a simulation study shows our approaches can significantly improve the network reliability, latency, and energy efficiency under dynamics.

EATDDS: Energy-aware middleware for wireless sensor and actuator networks

According to Object Management Group organization, Data Distribution Service (DDS) middleware is the leading technology for Industrial Internet of Things (IIoT). Therefore, using DDS-based middleware for Wireless Sensor/Actuator Networks (WSAN) will extremely ease the development and integration of WSAN applications into IIoT, which has an effective impact on improving the productivity and saving the cost. However, applying such technology over WSAN significantly affects the energy consumption. In this work, an energy-aware middleware for WSAN is developed based on DDS standard, which is called EATDDS. Furthermore, developing this middleware leads to a major enhancement into TOSSIM simulator; in which an Online Energy Model (OEM) is developed to make TOSSIM capable of developing and testing energy-aware protocols. The model is validated by comparing it against POWERTOSSIM. Our results show that EATDDS is efficient and can be accommodated with limited system resources.

ReViCEE: A recommendation based approach for personalized control, visual comfort & energy efficiency in buildings

Built-environment, especially open-plan workplaces are often not tailored to meet individual visual comfort needs. Therefore, meeting the need for personalized visual comfort whilst achieving energy efficiency in open-plan office environment has been an open challenge. However, recent technological advancements in distributed sensing, pervasive computing, context-awareness and machine learning is progressively closing this gap. This article introduces ReViCEE–a simple recommender systems based approach to learn both individual and collaborative user-preferences from historical data and offer recommendations for intelligent building lighting controls. The intelligence in this case is achieved by being able to derive set-points to control task lights such that it balances personalized visual comfort without compromising on energy savings. The proposed approach has been developed using Python and implemented on a real test-bed in an university campus office building in National University of Singapore. The evaluation of the proposed approach is carried out for two months using field experiments involving distributed wireless sensor actuator network (WSAN) and multiple occupants having varied visual sensation. The novelty lies in proposing a new inter-disciplinary approach that supports smart and intelligent buildings paradigm by learning and predicting optimum individual user-preferences towards energy efficient control of personalized light. The results obtained from field experiments present a potential energy savings upto 72% when compared to the conventional lighting systems used.

FLEET: When Time-Bounded Communication Meets High Energy-Efficiency

With the advent of low-cost, embedded sensor-actuator devices, the applications of cyber-physical systems have spread multi-fold in domains like infrastructure, manufacturing, automation, etc. Wireless sensor-actuator networks (WSANs) act as the backbone for applications in these domains. Typical WSAN deployments focus on energy-efficiency (in-turn lifetime) as replacing batteries is labor intensive and expensive. However, many CPS applications require highly-reliable data delivery with strict time bounds. Unfortunately, the classical approach of scheduling/prioritizing flows for bounded time communication is hard to implement with energy-constrained embedded devices. In this work, we present FLEET, a communication primitive that guarantees timely data delivery with 1) low latency by scheduling a maximum number of end-to-end flows within a short time span; 2) highly energy-efficient networking; and 3) reliable data delivery. Using a smart parallelization technique, FLEET achieves simultaneous transmissions while guaranteeing data delivery. This reduces the average duty-cycle of the nodes and makes it more energy-efficient than many state-of-the-art protocols. By combining multiple routing strategies, FLEET not only simplifies the schedulability problem but also accommodates more flows within a time span reducing delay considerably. Overall, with respect to the state of the art, FLEET offers a delay and duty cycling reduction by 2.2 and 2.8 times, respectively.

Reliable Middleware for Wireless Sensor-Actuator Networks

Many important and critical applications use wireless sensor/actuator networks (WSAN). These applications are spanning widely that range in several environments, including industrial, commercial, and residential. Most of these applications need a certain level of real-time communication in addition to reliable data delivery service. Data distribution service (DDS) is a known standard for supporting real-time distributed systems based on the publish/subscribe model. The DDS specification offers two disparate quality-of-service levels of data reliability, namely: best-effort and fully-reliable. TinyDDS is a lightweight and partial porting of DDS middleware to sensor-based platforms, specifically for platforms with limited resources. However, TinyDDS in its current form lacks the reliability support for data delivery. In this paper, we extended the DDS data reliability service and integrated it into TinyDDS, which resulted in Reliable TinyDDS. Moreover, we provide a prototype and comprehensive performance evaluation of the reliability functions taking into account: number of hops, number of publishers, and several other network parameters. The achieved results indicate that reliable data delivery in real-time for WSAN is possible with optimized system parameters, such as retransmission time-out value of 400ms and number of hops not exceeding 10 for an end-to-end delay ranging from 10 to 100s of milliseconds.

Scheduling Status Update for Optimizing Age of Information in the Context of Industrial Cyber-Physical System

Age of Information has been emerged as an interesting metric in real-time wireless networks that captures the freshness of information in the underlying applications. This topic is motivated by the problem in which the users of a network care about timely information defined as the age of the most recent status update a user has received. In the proposed work, we have studied this concept in the context of an industrial wireless sensor-actuator network for cyber-physical production systems. Such a network with ever-changing dynamics requires continuous updates of the system states and ongoing tasks by exchanging the time-critical, event-driven, and/or time-driven information to maintain the stability of the system, failing which may lead to shut down of the plant and other fatal consequences. Different real-time transmission scheduling algorithms manage how the channel resources are allocated each time depending on the packet arrivals to minimize the age of the information. However, unlike other real-time networks like broadcasting and sensor networks, etc. in cyber-physical systems, cyber and physical devices have different requirements to improve their quality of performance. Balancing between the performance criteria of both cyber and physical units seems to be a great challenge. In this work, the minimization of staleness of the real-time updates by minimizing the age of information and their effect on network performance have been studied extensively for this purpose. Two greedy scheduling policies have been proposed: one for the total age minimization and another one for stale age and jitter minimization. Their performances and complexities are compared with other existing scheduling algorithms. Moreover, the optimality of each of our proposed algorithms are proved analytically and claims are validated via simulation results too. Eventually, these results come to a conclusion that minimum age does not always guarantee the maximum freshness of information and satisfactory system performance at the same time.

Holistic Cyber-Physical Management for Dependable Wireless Control Systems

Wireless sensor-actuator networks (WSANs) are gaining momentum in industrial process automation as a communication infrastructure for lowering deployment and maintenance costs. In traditional wireless control systems, the plant controller and the network manager operate in isolation, which ignores the significant influence of network reliability on plant control performance. To enhance the dependability of industrial wireless control, we propose a holistic cyber-physical management framework that employs runtime coordination between the plant control and network management. Our design includes a holistic controller that generates actuation signals to physical plants and reconfigures the WSAN to maintain the desired control performance while saving wireless resources. As a concrete example of holistic control, we design a holistic manager that dynamically reconfigures the number of transmissions in the WSAN based on online observations of physical and cyber variables. We have implemented the holistic management framework in the wireless cyber-physicalsimulator (WCPS). A systematic case study is presented based on two five-state plants and a load positioning system using a 16-node WSAN. Simulation results show that the holistic management design has significantly enhanced the dependability of the system against both wireless interferences and physical disturbances, while effectively reducing the number of wireless transmissions.

Wireless Sensor-Actuator Network for Cell-Level Treatment Based on Protocol of Collision Segregation via Learning

State-of-the-art technology of nano-sensors and actuators enables diagnostics and treatment on the scale of biological cells. However, an advanced medical application should allow the direct feedback of a sensed signal to an actuation, e.g., an action potential propagation through an axon or a special cell activity might be sensed and suppressed by an actuator through voltage stimulation or chemical agent delivery. Such a complex procedure calls for building a communication network between sensors and actuators, but is challenged with issues, such as intensive signal collisions, protocol simplification, and communication efficiency. We propose a collision segregation method and the protocol of collision segregation via learning. Simulations of stress tests show its advantages as compared to the performance of the traditional methods for wireless body area networks. The potential applications are discussed in detail, such as photothermal cancer therapy and anti-cancer drug delivery.

Wireless sensor-actuator network as a part of the cyber-physical system

Розглянуто проблему розроблення бездротової мережі сенсорних та виконавчих вузлів у складі кіберфізичної системи (КФС). Проаналізовано способи реалізації схеми бездротового зв’язку. Запропоновано структуру та алгоритми роботи мережі. Наведено результати реалізації сенсорних та виконавчих вузлів мережі.

A Rule Verification System for Smart Buildings

As an important component of Internet of Things (IoT), wireless sensor-actuator networks can significantly improve the practicality and flexibility of smart building systems. In smart building systems, services, stored as rules, are achieved by rule analyzing and executing. However, the irrational contents of rules and the conflicts among rules may bring confusion and maloperation in the system. To verify the correctness of rules, we propose a lightweight rule verification and resolution framework which mainly include: 1) a rule verification system for content anomaly detection and rule conflict detection by using domain knowledge and probability analysis and 2) a quick resolution strategy for rule conflicts based on conflict-scenario-analysis. This framework can balance the verification quality with speed and guarantee that the rule system performs appropriately. Moreover, in order to reduce the comparison in rule verification, we apply a tree structure to store the building structure hierarchically and bind every rule to one node in the location tree. This way, the position information of a rule can be extracted, and the verification efficiency can be improved. The experimental results show that our proposed framework and strategies can perform efficiently and flexibly in a smart building system.

Empirical Study and Enhancements of Industrial Wireless Sensor–Actuator Network Protocols

Wireless sensor–actuator networks (WSANs) offer an appealing communication technology for process automation applications to incorporate the Internet of Things (IoT). In contrast to other IoT applications, process automation poses unique challenges for industrial WSAN due to its critical demands on reliable and real-time communication. While industrial WSANs have received increasing attention in the research community recently, most published results to date have focused on the theoretical aspects and were evaluated based on simulations. There is a critical need for experimental research on this important class of WSANs. We developed an experimental testbed by implementing several key network protocols of WirelessHART, an open standard for WSANs that has been widely adopted in the process industries based on the HART. We then performed a series of empirical studies showing that graph routing leads to significant improvement over source routing in terms of worst-case reliability, but at the cost of longer latency and higher energy consumption. It is therefore important to employ graph routing algorithms specifically designed to optimize latency and energy efficiency. Our studies also suggest that channel hopping can mitigate the burstiness of transmission failures; a larger channel distance can reduce consecutive transmission failures over links sharing a common receiver. Based on these insights, we developed a novel channel hopping algorithm that utilizes far away channels for transmissions. Furthermore, it prevents links sharing the same destination from using channels with strong correlations. Our experimental results demonstrate that our algorithm can significantly improve network reliability and energy efficiency.

Research on Wireless Sensor Actuator Distribution Algorithm Meeting Maximum Request Expectation

In wireless sensor actuator networks, actuator nodes are very important to network coverage for wireless sensor. So according to the characteristics that wireless communication is easy to be affected by the environment, in this wireless sensor actuator network the actuator nodes are abstracted to be service providers and the sensor nodes are abstracted to be service consumers. Furthermore, the messages transferred from actuator nodes to sensor nodes are abstracted to be service requests and the coverage of sensor nodes by actuator nodes is service providing. Moreover, the service faulty ratio of actuator nodes is defined in this paper. Based on that, an actuator node coverage algorithm that satisfies the maximum request expectation is put forwarded. Its goal is to solve the mathematical expectation of maximizing the number of service requests with fixed number of sensor nodes and actuator nodes. So the optimal position of actuator nodes could be identified. The theoretic proof and simulation result show that this algorithm is more efficient compared with similar algorithms

Implementation and Assessment of a Decentralized Load Frequency Control: Application to Power Systems with High Wind Energy Penetration

This paper describes and assesses a decentralized solution based on a wireless sensor-actuator network to provide primary frequency control from demand response in power systems with high wind energy penetration and, subsequently, with relevant frequency excursions. The proposed system is able to modify the electrical power demand of a variety of thermostatically-controlled loads, maintaining minimum comfort levels and minimizing both infrastructure requirements and primary reserves from the supply side. This low-cost hardware solution avoids any additional wiring, extending the wireless sensor-actuator network technology towards small customers, which account for over a 30% share of the current power demand. Frequency excursions are collected by each individual load controller, considering not only the magnitude of the frequency deviation, but also their evolution over time. Based on these time-frequency excursion characteristics, controllers are capable of modifying the power consumption of thermostatically-controlled loads by switching them off and on, thus contributing to primary frequency control in power systems with higher generation unit oscillations as a consequence of relevant wind power integration. Field tests have been carried out in a laboratory environment to assess the load controller performance, as well as to evaluate the electrical and thermal response of individual loads under frequency deviations. These frequency deviations are estimated from power systems with a high penetration of wind energy, which are more sensitive to frequency oscillations and where demand response can significantly contribute to mitigate these frequency excursions. The results, also included in the paper, evaluate the suitability of the proposed load controllers and their suitability to decrease frequency excursions from the demand side in a decentralized manner.