High reliability wireless communications for mission-critical applications often necessitates path diversity through redundant channels. In this context, we explore the combination of the IEC 62439 High-availability Seamless Redundancy (HSR) architecture with IEEE 802.1CB Frame Replication and Elimination for Reliability (FRER) features. While HSR is well-established for wired networks, both HSR and FRER aim to enhance network reliability through redundancy. However, the HSR algorithm assumes frame ordering, which is impractical in wireless networks due to packet ordering and time-based elimination challenges. To address this, we propose integrating the IEEE 802.1CB vector recovery algorithm within the HSR framework. We focus on Wireless Local Area Networks (WLANs), where we modify an existing HSR implementation in Linux to operate over wireless channels. Our experimental analysis demonstrates significant improvements in latency metrics compared to non-redundant communications subject to interfering traffic. The proposed implementation targets industrial applications, such as robotic feedback control with stringent two-millisecond latency deadlines. By considering latency and out-of-order delivery—features not well-supported by the current HSR standard, we demonstrate improved reliability and latency characteristics required for demanding real-time control applications utilizing wireless as a principal communications medium.

Time-sensitive networking (TSN) is emerging as a viable means to achieving deterministic quality of service (QoS) communications within mission critical industrial applications such as feedback control systems, robotics, and precision sensing and actuation. Originally developed for Ethernet-based audio-video applications using the User Datagram Protocol (UDP). TSN assume unidirectional flows from source (talked) to destination(listener) and it is most easily implemented using UDP in which packets are transmitted without an acknowledgment from the recipient. However, most existing industrial protocols are implemented using the reliable Transport Control Protocol (TCP) in which each transmission is explicitly acknowledged. In this work, a bandwidth efficient TSN schedule is developed to accommodate the TCP traffic flow between two synchronized robots collaboratively moving an object. We then demonstrate an IEEE 802.1Qbv TSN schedule over an IEEE 802.11 wireless medium that guarantees robot performance requirements are maintained while accommodating concurrent best-effort traffic flows. The process for schedule selection and experimental data collection is discussed, and TSN configuration parameter tuning and experimental results are provided.

Time-sensitive networking (TSN) is an emerging topic for the advancement of wireless networking for industrial applications. TSN, as defined under the umbrella of IEEE 802.1 working group standards, addresses issues related to providing deterministic communications over IEEE 802-based Local Area Networks (LANs). TSN was originally designed to support real-time audio/video applications over Ethernet providing better reliability and lower, more deterministic latency with traffic shaping capabilities. TSN has since expanded its scope and applicability to other applications such as those in industrial environments and automotive applications. Industrial examples include machine-machine communications for robot control, end-effector actuation, real-time sensing, and safety integrated systems. Applications utilizing a wireless local area network (WLAN) can also benefit from scheduling and traffic shaping as defined in the 802.1Qbv standard; however, factors such as clock stability, synchronization, resource requirements and protocol options come into play when selecting a schedule to support multiple application types on the same network. In this article, we present a scenario for a collaborative robot heavy lift operation, in which, two robots communicate over an IEEE 802.11 WLAN with TSN capabilities to lift a rigid body in three dimensions. Scheduling is performed using 802.1Qbv over WLAN with the robot operating system (ROS) used as the software middleware utilizing the transport control protocol (TCP). As a part of the research, we describe our process for schedule selection to accommodate the time-sensitive traffic of the robotic scenario while allowing an industrial internet of things (IIoT) high data rate traffic to coexist. We then provide an analysis of the impacts of TSN schedule selection on the operational performance of the collaborative robot application.

In this article, we describe a methodology and associated models to evaluate a time sensitive collaborative robotics application enabled by wireless time sensitive networking (WTSN) capabilities. We also present a method to configure WTSN scheduling to meet the application time budget and validate it in a realistic industrial use case. We detail the methodologies for implementing and characterizing the performance of key WTSN capabilities, namely time synchronization and time-aware scheduling, over an IEEE 802.11 based network. We deploy the WTSN capabilities with a collaborative robotic workcell consisting of two robotic arms, which emulate a material handling application, known as machine tending. We further explore configurations and measurement methodologies to characterize application performance of this use case and correlate it to the performance of the wireless network.

Industrial wireless plays a crucial role in cyber-physical system (CPS) advances for the future vision of smart manufacturing. However, industrial wireless environments are different from each other and are different from home and office environments. Hence, industrial wireless channel modeling is essential for the development of industrial wireless systems. Moreover, millimeter-wave (mmWave) wireless bands have a high potential to be used for the high data-rates required for industrial automation reliability, with multiple antennas envisioned to mitigate the high path loss. As a result, in this work, we introduce a machine learning (ML) based exemplar extraction approach on mmWave wireless spatial-channel measurements. The proposed approach processes the measured power-angle-delay-profiles to cluster them into a number of groups with respect to the angle of arrival. Then, an exemplar power-delay-profile (PDP) is extracted to represent each group. The resulting set of exemplars provide a tractable way to conduct mmWave industrial wireless systems testing and evaluation by compactly representing various feature groups. This allows the assessment of wireless equipment over the exemplars without the need to test over all of the different instances of wireless channel paths.

For accurate characterization and evaluation of wireless mechatronic systems, effective modeling of wireless communication channels is of paramount importance, especially to simulation-oriented methods. Conventional simulation methods employ mathematical models to abstract details of prototype channels. Although such mathematical models often have rigorous theoretical underpinnings, they can be weak in capturing complex environmental characteristics and complex forms of diversity that are exhibited in industrial communication environments. To address this problem, we develop, in this paper, a new approach to deriving effective simulation models for industrial communication channels. Our approach involves field measurements from actual wireless mechatronic environments together with feature extraction from the measurements, and data-driven classification based on the extracted features. Our approach leads to a general framework for simulating wireless mechatronic systems in a way that realistically incorporates the complex channel characteristics of these systems.

In this paper, we describe a collaborative robotic workcell testbed enabled by Wireless Time Sensitive Networking (WTSN) technologies and discuss deployment, performance measurement and management guidelines challenges. We detail the methodologies for implementing and characterizing the performance of key WTSN capabilities (time synchronization and time-aware scheduling) over IEEE 802.11/Wi-Fi. We deployed WTSN capabilities on the National Institute of Standards and Technology (NIST) collaborative robotic workcell testbed consisting of two robotic arms that emulates a material handling application, known as machine tending. We further explore configurations and measurement methodologies to characterize Quality of Experience (QoE) of this use case and correlate it to the performance of the wireless network.

Efficient and accurate simulation methods are of increasing importance in the design and evaluation of factory communication systems. Model-based simulation methods are based on formal models that govern the interactions between components and subsystems in the systems that are being simulated. The formal models facilitate systematic integration across the system, and enable powerful methods for analysis and optimization of system performance. However conventional simulation approaches utilize communication channel models that do not fully reflect the characteristics and diversity of industrial communication channels. To help bridge this gap, we develop in this paper new methods for channel model construction for link-layer simulation that systematically incorporate field measurements of wireless communication channels from industrial networks, and derive corresponding channel modeling library components. The generated library components capture channel characteristics in the form of lookup tables, which can be flexibly integrated into system-level simulators or co-simulation tools. We integrate our new table-generation methods into a model-based co-simulator that jointly simulates the interactions among process flows, physical layouts of workcells, and communication channels in factory systems that are integrated with wireless networks. Experimental results using our lookup-table-augmented co-simulator demonstrate the utility of the proposed methods for flexibly and accurately integrating realistic industrial network channel conditions into simulation processes.

Wireless communication is gaining popularity in the industry for its simple deployment, mobility, and low cost. Ultralow latency and high reliability requirements of mission-critical industrial applications are highly demanding for wireless communication, and the indoor industrial environment is hostile to wireless communication due to the richness of reflection and obstacles. Assessing the effect of the industrial environment on the reliability and latency of wireless communication is a crucial task, yet it is challenging to accurately model the wireless channel in various industrial sites. In this article, based on the comprehensive channel measurement results from the National Institute of Standards and Technology at 2.245 and 5.4 GHz, we quantify the reliability degradation of wireless communication in multipath fading channels. A delay optimization based on the channel characterization is then proposed to minimize packet transmission times of a cyclic prefix orthogonal frequency division multiplexing system under a reliability constraint at the physical layer. When the transmission bandwidth is abundant and the payload is short, the minimum transmission time is found to be restricted by the optimal cyclic prefix duration, which is correlated with the communication distance. Results further reveal that using relays may, in some cases, reduce end-to-end latency in industrial sites, as achievable minimum transmission time significantly decreases at short communication ranges.

The wireless devices in cyber-physical systems (CPS) play a primary role in transporting the information flows within such systems. Deploying wireless systems in industry has many advantages due to lower cost, ease of scale, and flexibility due to the absence of cabling. However, industrial wireless deployments in various industrial environments require having the proper models for industrial wireless channels. In this work, we propose and assess an algorithm for characterizing measured channel impulse response (CIR) of time-varying wireless industrial channels. The proposed algorithm performs data processing, clustering, and averaging for measured CIRs. We have deployed a dynamic time warping (DTW) distance metric to measure the similarity among CIRs. Then, an affinity propagation (AP) machine learning clustering algorithm is deployed for CIR grouping. Finally, we obtain the average CIR of various data clusters as a representation for the cluster. The algorithm is then assessed over industrial wireless channel measurements in various types of industrial environments. The goal of this work is to have a better industrial wireless channels representation that results in a better recognition to the nature of industrial wireless communications and allows for building more effective wireless devices and systems.

Industrial Internet of Things (IIoT) applications, featured with data-centric innovations, are leveraging the observability, control, and analytics, as well as the safety of industrial operations. In IIoT deployments, wireless links are increasingly used in improving the operational connectivity for industrial data services, such as collecting massive process data, communicating with industrial robots, and tracking machines/parts/products on the factory floor and beyond. The wireless system design for IIoT applications is inherently a joint effort between operational technology (OT) engineers, information technology (IT) system architects, and wireless network planners. In this paper, we propose a new reference framework for the wireless system design in IIoT use cases. The framework presents a generic design process and identifies the key questions and tools of individual procedures. Specifically, we extract impact factors from distinct domains including industrial operations and environments, data service dynamics, and the IT infrastructure. We then map these factors into function clusters and discuss their respective impact on performance metrics and resource utilization strategies. Finally, discussions take place in four exemplary IIoT applications where we use the framework to identify the wireless network issues and deployment features in the continuous process monitoring, discrete system control, mobile applications, and spectrum harmonization, respectively. The goals of this work are twofold: 1) to assist OT engineers to better recognize wireless communication demands and challenges in their plants, 2) to help industrial IT specialists to come up with operative and efficient end-to-end wireless solutions to meet demanding needs in factory environments.

While attacks on information systems have for most practical purposes binary outcomes (information was manipulated/eavesdropped, or not), attacks manipulating the sensor or control signals of Industrial Control Systems (ICS) can be tuned by the attacker to cause a continuous spectrum in damages. Attackers that want to remain undetected can attempt to hide their manipulation of the system by following closely the expected behavior of the system, while injecting just enough false information at each time step to achieve their goals. In this work, we study if attack-detection can limit the impact of such stealthy attacks. We start with a comprehensive review of related work on attack detection schemes in the security and control systems community. We then show that many of those works use detection schemes that are not limiting the impact of stealthy attacks. We propose a new metric to measure the impact of stealthy attacks and how they relate to our selection on an upper bound on false alarms. We finally show that the impact of such attacks can be mitigated in several cases by the proper combination and configuration of detection schemes. We demonstrate the effectiveness of our algorithms through simulations and experiments using real ICS testbeds and real ICS systems.

Factory and process automation systems are increasingly employing information and communications technologies to facilitate data sharing and analysis in integrated control operations. Wireless connections provide flexible access to a variety of field instruments and reduce network installation and maintenance costs. This serves as an incentive for the adoption of industrial wireless networks based on standards such as the WirelessHART and ISA100.11a in factory control systems. However, process control systems vary greatly and have diverse wireless networking requirements in different applications. These requirements include deterministic transmissions in the shared wireless bandwidth, low-cost operation, long-term durability, and high reliability in the harsh radio propagation environment. It is an open question whether a generic wireless technology would meet the requirements of industrial process control. In this paper, we propose a novel simulation framework for performance evaluation of wireless networks in factory and process automation systems. We select a typical process control plant model, specifically the Tennessee Eastman Challenge (TE) Model, and define the interfaces between the process simulator and the wireless network simulator. We develop a model of the protocol stack of the WirelessHART specification in the OMNET++ simulation engine as a typical industrial wireless network. We present simulation results that validate the prospect of using WirelessHART in the TE plant, and we evaluate the impact of various wireless network configurations on the plant operation. Given its modular design, the proposed simulation framework can be easily used to evaluate the performance of other industrial wireless networks in conjunction with a variety of process control systems.