Time-Sensitive Networking (TSN) has been recognized as one of the key enabling technologies for Industry 4.0 and has been deployed in many mission- and safety-critical applications e.g., automotive and aerospace systems. Given the stringent real-time requirements of these applications, the Time-Aware Shaper (TAS) draws special attention among TSN's many traffic shapers due to its ability to achieve deterministic timing guarantees. Many scheduling methods for TAS shapers have been recently developed that claim to improve system schedulability. However, these scheduling methods have yet to be thoroughly evaluated, especially through experimental comparisons, to provide a systematical understanding of their performance in diverse application scenarios. In this paper, we fill this gap by presenting a systematic review and experimental study on existing TAS-based scheduling methods for TSN. We first categorize the system models employed in these works along with the specific problems they aim to solve, and outline the fundamental considerations in the designs of TAS-based scheduling methods. We then perform an extensive evaluation on 17 representative solutions using both high-fidelity simulations and a real-life TSN testbed, and compare their performance under both synthetic scenarios and real-life industrial use cases. Through these studies, we identify the limitations of individual scheduling methods and highlight several important findings. We expect this work will provide foundational knowledge and performance benchmarks needed for future studies on real-time TSN scheduling.

Applying high-speed real-time wireless technologies in industrial applications has the great potential to reduce the deployment and maintenance costs compared to their wired counterparts. Wireless technologies enhance the mobility and reduce the communication jitter and delay for mobile industrial equipment, such as mobile collaborative robots. Unfortunately, most existing wireless solutions employed in industrial fields either cannot support the desired high-speed communications or cannot guarantee deterministic, real-time performance. A more recent wireless technology, RT-WiFi, achieves a good balance between high-speed data rates and deterministic communication performance. It is however developed on commercial-of-the-shelf (COTS) hardware, and takes considerable effort and hardware expertise to maintain and upgrade. To address these problems, this paper introduces the software-defined radio (SDR)-based RT-WiFi solution which we call SRT-WiFi. SRT-WiFi provides full-stack configurability for high-speed real-time wireless communications. We present the overall system architecture of SRT-WiFi and discuss its key functions which achieve better timing performance and solve the queue management and rate adaptation issues compared to COTS hardware-based RT-WiFi. To achieve effective network management with rate adaptation in multi-cluster SRT-WiFi, a novel scheduling problem is formulated and an effective algorithm is proposed to solve the problem. A multi-cluster SRT-WiFi testbed is developed to validate the design, and extensive experiments are performed to evaluate the performance at both device and system levels.

Smart factory automation has an ongoing trend to employ high-speed real-time wireless technologies to interconnect heterogeneous industrial assets to perform various sensing and control services, and support mobile equipment to conduct designated tasks in a collaborative fashion. Applications in automation industries usually have stringent requirements on both high data rates and deterministic real-time performance. Existing efforts, however, either cannot meet the performance requirements or are based on commercial-off-the-shelf (COTS) hardware and cannot provide full-stack configurability [1].

Blockchain is a distributed and decentralized ledger for recording transactions. It is maintained and shared among the participating nodes by utilizing cryptographic primitives. A consensus protocol ensures that all nodes agree on a unique order in which records are appended. However, current blockchain solutions are facing scalability issues. Many methods, such as Off-chain and Directed Acyclic Graph (DAG) solutions, have been proposed to address the issue. However, they have inherent drawbacks, e.g., forming parasite chains. Performance, such as throughput and latency, is also important to a blockchain system. Sharding has emerged as a good candidate that can overcome both the scalability and performance problems in blockchain. To date, there is no systematic work that analyzes the sharding protocols. To bridge this gap, this paper provides a systematic and comprehensive review on blockchain sharding techniques. We first present a general design flow of sharding protocols and then discuss key design challenges. For each challenge, we analyze and compare the techniques in state-of-the-art solutions. Finally, we discuss several potential research directions in blockchain sharding.

Process industries cover a wide set of industries, in which the processes are controlled by a combination of distributed control systems (DCSs) and programmable logic controllers (PLCs). These control systems utilize various measurements such as pressure, flow, and temperature to determine the state of the process and then use field devices such as valves and other actuating devices to manipulate the process. Since there are many different types of field devices and since each device is calibrated to its specific installation, when monitoring devices, it is important to be able to transfer not only the device measurement and diagnostics but also characteristics about the device and the process in which it is installed. The current monitoring architecture, however, creates challenges for continuous monitoring and analysis of diagnostic data. In this paper, we present the design of an Industrial Internet-of-Things (IIoT) system for supporting large-scale and continuous device condition monitoring and analysis in process control systems. The system design seamlessly integrates existing infrastructure [e.g., highway addressable remote transducer (HART) and WirelessHART networks, and DeltaV DCS] and newly developed hardware/software components (e.g., one-way data diode and IoT cellular architecture) together for control network data collection and streaming of the collected device diagnostic parameters to a private cloud to perform streaming data analytics designed for fault identification and prediction. A prototype system has been developed and supported by Emerson Automation Solutions and deployed in the field for design validation and long-term performance evaluation. To the best of our knowledge, this is the first ever publicly reported effort on IoT system design for process automation applications. The design can be readily extended for condition monitoring and analysis of many other industrial facilities and processes.

A demonstration of a field gateway design that can be configured through a web interface to collect data from multiple data sources using different protocols and stream to cloud based analytics platform.

6TiSCH network architecture has recently been introduced to combine the high reliability and low-power consumption of the TSCH (Time-Slotted Channel Hopping) mode of IEEE 802.15.4e MAC with the ease of integration offered by the IP-enabled upper layer protocols. 6TiSCH network uses RPL (Routing Protocol for Low Power and Lossy Networks) as its routing protocol to manage the network layer functionalities. RPL however is vulnerable to internal routing attacks such as Rank attack where a malicious node multicasts a fake position (Rank) or a fake path cost toward the sink node to lure nearby nodes to forward their packets through it. In this paper, we propose a hybrid specification-based intrusion detection system (IDS) that consists of centralized and distributed modules installed on the sink and RPL nodes respectively to prevent nodes from selecting an intruder as their successors. The proposed method also eliminates intruders' chances of becoming a time source and disrupt the synchronization of 6TiSCH networks. The results from our extensive simulations show that compared with existing countermeasures, the proposed IDS can effectively protect RPL topologies while only incurring limited network management overhead.

This paper discusses the techniques necessary to implement the InES Linux based IEC 62439-3 (PRP) protocol as a software module within the QNX networking driver environment, which also supports non-PRP traffic simultaneously. Comparisons to other implementations of the PRP stack are discussed. We leverage the NetBSD-based network stack implementation of QNX, and discuss common API calls which are suitable to implement a dual-mode PRP driver for QNX. The software behavior for ingress, egress, and management traffic specific to PRP is discussed at the API level. We show the CPU utilization performance of the PRP network as compared to non-PRP networks, along with QNX microkernel specific concerns. Caveats to this approach and mitigations are discussed.

We designed a crossdevice testing and reporting system, called cross-device testing and reporting system (CD-TRS), to facilitate the functional validation of protocol and application design in large-scale RTWNs. CD-TRS leverages the nice property of RTWNs that all devices in the network are fully synchronized. By specifying and retrieving events and device status from multiple devices in the runtime simultaneously, CD-TRS can further assemble them into a network-wide report on the detailed system behavior by aligning the records according to their associated network timestamps (or absolute slot number (ASN) in most RTWNs). By comparing this runtime network behavior report with the required protocol and application specifications, abnormal device/network behavior can be observed and their root cause(s) can be effectively located. This thus can significantly reduce the complexity of RTWN testing and reporting. In the following, we first describe the overall architecture of CD-TRS, and then demonstrate how CD-TRS helps with the functional validation of D2-PaS, a distributed and dynamic packet scheduling framework we recently developed for handling disturbances in real-time wireless networks.

Real-time wireless sensor and actuator networks (WSANs) have experienced widespread adoption across many industries due to their great advantages of enhanced mobility, easier deployment as well as reduced configuration and maintenance costs. To compensate for the dynamic and unpredictable nature of wireless networks, extensive research efforts have been devoted on algorithm design for efficient network resource management to both meet robustness requirements and optimize the overall network for latency, power, and throughput. Very limited results, however have been reported for the network performance in real field deployments. This paper presents an in-depth exploration of a WirelessHART mesh network deployed in a separations research facility. To understand how the network performs under different scenarios it is restarted and data traces are collected at three points in time with different experiment settings. We examine the impact of initial neighbor selection and observe the network manager adapting the network. The mesh network performance is reported in terms of its primary functions, which are to report process measurements and maintain the network operations.

Wireless sensing and networking technologies have taken a strong foothold in the process control industry. The focus has now shifted towards applying control with wireless technology. As such, the current industrial wireless sensor network architectures are under increased scrutiny about their real-time, reliability, and security performances. In this paper, we take a renewed look at network synchronization, the basic building block to support real-time activities. We present our analysis, key observations, and recommendations. We also get into the depth of WirelessHART, the most deployed industrial wireless network architecture, and affirm that, with good practice, we could achieve highly reliable synchronization to provide guaranteed packet deliveries. The correctness of the time synchronization analysis in both line and mesh network topologies is verified through extensive simulation experiments.

Localization in wireless sensor networks is an important functionality that is required for tracking personnel and assets in industrial environments, especially for emergency response. Current commercial localization systems such as GPS suffer from the limitations of either high cost or low availability in many situations (e.g., indoor environments that exclude direct line-of-sight signal reception). The development of industrial wireless sensor networks such as WirelessHART provides an alternative. In this article, we present the design and implementation of ColLoc: a collaborative location and tracking system on WirelessHART as an industrially viable solution. This solution is built upon several technological advances. First, ColLoc adds the roaming functionality to WirelessHART and thus provides a means for keeping mobile WirelessHART devices connected to the network. Second, ColLoc employs a collaborative framework to integrate different types of distance measurements into the location estimation algorithm by weighing them according to their precision levels. ColLoc adopts several novel techniques to improve distance estimation accuracy and decreases the RSSI presurvey cost. These techniques include introducing distance error range constraints to the measurements, judiciously selecting the initial point in location estimation and online updating the signal propagation models in the anchor nodes, integrating Extended Kalman Filter (EKF) with trilateration to track moving objects. Our implementation of ColLoc can be applied to any WirelessHART-conforming network because no modification is needed on the WirelessHART field devices. We have implemented a complete ColLoc system to validate both the design and the effectiveness of our localization algorithm. Our experiments show that the mobile device never drops out of the WirelessHART network while moving around; with the help of even one dependable anchor, using RSSI can yield at least 75% of distance errors below 5 meters, which is quite acceptable for many typical industrial automation applications.

The Internet of Things (IoT) is considered to be the biggest challenge and opportunity for the Internet today. The Internet of Things makes it possible to connect embedded devices in physical environments to the Internet and interact with those devices through both IP and web interfaces. As a subset of the Internet of Things, the wireless embedded Internet targets at enabling resource-limited wireless devices with IP functions and connecting them to the Internet through low-power and low-bandwidth wireless networks. In this paper, we describe our design of the network infrastructure of wireless embedded Internet for industrial automation, and present the implementation and demonstration of a prototype system which integrates WirelessHART mesh networks into the Internet and supports web-based monitoring and control services.

WirelessHART™ was released in September 2007 and became an IEC standard in April 2010 (IEC 62591). It is the first open wireless communication standard specifically designed for process measurement and control applications deployed in harsh and noisy environments. WirelessHART distinguishes itself from other public standards by maintaining a central Network Manager. The Network Manager is responsible for maintaining up-to-date routes and communication schedules for the network, thus guaranteeing the reliable and real-time network communications. To deal with the intensive computation requirement in a centralized WirelessHART Network Manager, particularly of middle or large scale network sizes, in this article, we utilize parallelization techniques to implement the Network Manager on embedded multicore architectures. By leveraging the multicore capabilities of the AMD Embedded G-Series Dual-Core processor, we utilize the Texas Multicore Technologies' (TMT) SequenceL™ language and runtime environment to parallelize the algorithms proposed in our previous work for constructing reliable routing graphs and real-time communication schedule. Our experiments show that AMD Embedded G-Series is an ideal platform for medium to large size WirelessHART network and SequenceL™ language can help significantly reduce the development cycle and further improve the algorithm efficiency and system performance in embedded multicore architectures.

Wireless applications in process automation started in areas where wireless sensors provide rich process information to the automation systems. Shortly after WirelessHART became the international standard, both ISA100.11a and WirelessHART claimed that their respective wireless technology could be applied to control as well. Although both standards provide provisions for supporting control over wireless, actual installations of wireless control systems have been slow to be adopted. Due to people's wariness of using wireless in combination with the serious nature of control, what is needed is a demonstration of performance and reliability of control when being executed across wireless media. A good starting point is a comparison between a wireless control system and its wired counterpart. In this paper we first study if we can establish a WirelessHART control loop the same way as a wired one; then we study if our WirelessHART control loop could achieve the same execution rates and reliability as a wired Foundation Fieldbus control loop. The experiment affirms that, in most likely cases, control over a WirelessHART network could be as good as control over a wired fieldbus.

Localization in wireless sensor networks is an important functionality that is required for tracking personnel and assets in industrial environments, especially for emergency response. Current commercial localization systems such as GPS suffer from the limitations of either high cost or low availability in many situations (e.g., in-door environments that exclude direct line-of-sight signal reception). The development of industrial wireless sensor networks such as Wireless Hart provides an alternative. In this paper, we present the design and implementation of Roaming Hart: a collaborative localization system on Wireless Hart as an industrially viable solution. This solution is built upon several technological advances. First, Roaming Hart adds the roaming functionality to Wireless Hart and thus provides a means for keeping mobile Wireless Hart devices connected to the network. Second, Roaming Hart employs a collaborative framework to integrate different types of distance measurements into the location estimation algorithm by weighing them according to their precision levels. Roaming Hart adopts several novel techniques to improve distance estimation accuracy and decreases the RSSI pre-survey cost. These techniques include introducing distance error range constraints to the measurements, judiciously selecting the initial point in location estimation and on line updating the signal propagation models in the anchor nodes. Our implementation of Roaming Hart can be applied to any Wireless Hart-conforming network because no modification is needed on the Wireless Hart field devices. We have implemented a complete Roaming Hart system to validate both the design and the effectiveness of our localization algorithm. Our experiments show that the mobile device never drops out of the Wireless Hart network while moving around, with the help of even one dependable anchor, using RSSI can yield at least 75% of distance errors below 5 meters, which is quite acceptable for many typical industrial automation applications.

The traditional sampling method in process control systems is based on a periodic task model. This is because controllers are executed in a strictly periodic manner. Sensors sample the process data and send it periodically to the appropriate controllers through a communication system such as the field bus. Since the field bus is shared by multiple sensors, there is some delay (control loop latency)between the sampling and control actions. In order to minimize the control loop latency, a higher than necessary sampling frequency is typically adopted, which results in unnecessary waste of energy. In this paper, we propose Min Max: a sampling interval control algorithm for tackling this problem. In Min Max, sampling tasks are not periodic but have both maximum and minimum distance constraints. This sampling model has advantages that are especially important in the domain of wireless control for industrial automation. We shall then discuss the jitter property of sampling schemes under this model and propose algorithms for controlling the sampling intervals of sensors in terms of the Min Max problem (UMin Max) which we shall introduce. Though this problem is NP-hard in general, even for special case of unit-time tasks, we show how to reduce Min Max to well-studied scheduling models such as Liu and Layland-type periodic models and pinwheel models, at the expense of some loss of schedulability. These reductions allow us to derive efficient schedulability tests that can be used to solve the sampling interval control problem in practice. Simulations are used to compare the performance of different UMin Max schedulers in two key figures of merit: the acceptance ratio and the jitter ratio. Simulation of a process control system model also shows that UMin Max can reduce about 40% of the traffic load on the communication system which is especially important for energy-aware wireless process control applications.

Industrial wireless mesh networks are deployed in harsh and noisy environments for process measurement and control applications. Compared with wireless community networks, they have more stringent requirements on communication reliability and real-time performance. Missing or delaying of the process data by the network may severely degrade the overall control performance. In this paper, we abstract the primary reliability requirements in typical industrial wireless mesh networks and define three types of reliable routing graphs for different communication purposes. We present efficient algorithms to construct them and describe the recovery mechanisms in the event of component failures. Based on these graphs, data link layer communication schedules are generated to achieve end-to-end real-time performance. We demonstrate through extensive experimental results that our algorithms can achieve highly reliable routing, improved communication latency and stable real-time communication in large-scale networks at the cost of modest overhead in device configuration.

Unlike wired networks, the configuration and the behavior of wireless networks are heavily dependent on many environmental factors. While this makes it more difficult to build a wireless network testbed whose behavior is controllable, it also makes the availability of such a testbed all the more desirable. Indeed, the difficulties in building a good wireless mesh testbed belie the fact that most research work on mesh network performance is backed up only by computer simulations. In this paper, we present a practical design philosophy in which a realistic and controllable wireless mesh network testbed is built with a relatively small deployment of physical equipments by exploiting the idea of a virtual network. Specifically, we simulate a virtual network within the testbed and use one physical wireless transceiver to simulate multiple virtual devices. An observer who only reads the transmitted wireless messages will not be able to tell the difference from a real wireless mesh. Our approach has been adopted in a recent industry-standard testing suite, namely, Wi-HTest. In this paper, we shall discuss our experience in building Wi-HTest by applying the virtual network approach.

WirelessHART was released in September 2007 and is the first open wireless communication standard specifically designed for real-time process control applications. It is designed to the same standards as its wired counterpart for reliability and interoperability. To ensure the compliance with the HART Communication Protocol and the adherence to its strict timing requirements, all WirelessHART devices must be thoroughly tested and registered with the HART Communication Foundation (HCF). In this paper, we present Wi-HTest, the test suite designed to exercise WirelessHART devices, thus facilitating compliance assessment. We discuss the detailed architecture of Wi-HTest and highlight several critical features like packet handling with accurate timing control and fault data injection. We also describe a sniffer called Wi-Analys for capturing WirelessHART packets along with their timing information and a post process suite for analyzing the packets. These three tools together provide the complete compliance verification environment for WirelessHART. Based on the test specification developed by HCF, a representative test case is conducted for the purpose of demonstration. This test case in turn shows that Wi-HTest is a novel and efficient test suite for verifying the compliance of real-time WirelessHART devices.

WirelessHART is an emerging wireless communication standard that is targeted at the real-time process control industry.An example application of wireless communication in an industrial process control plant is the location of field engineers. The capability to locate personnel is a safety critical issue in process control plants because of high risks posed by toxic chemicals and other hazards. This paper presents the design, implementation and evaluation of a location-aware application built upon WirelessHART. The aim of this application is to locate a mobile device (and thus the person carrying the device) via the deployed WirelessHART network. The application is a software-based - no device modifications are required. Consequently, it is applicable to any WirelessHART network. In this application, both the mobile device (a handheld device or a badge carried by a worker) and field devices (attached to the plant process) periodically send health reports of their neighbors to the network manager. The network manager analyzes these reports and discards the untrustworthy pairs through comparison. Next, the network manager feeds the average received signal indications to a well-trained radio propagation model to derive the location. To evaluation our solution, several preliminary experiments are carried out and the results are very promising, with a median error less than 4 meters, which is good enough for the industrial requirement. To the best of our knowledge, this is the first attempt to develop location-aware application in WirelessHART networks.

Wireless technology has been regarded as a paradigm shifter in the process industry. The first open wireless communication standard specifically designed for process measurement and control applications, WirelessHART was officially released in September 2007 (as a part of the HART 7 Specification). WirelessHART is a secure and TDMA-based wireless mesh networking technology operating in the 2.4GHz ISM radio band. In this paper, we give an introduction to the architecture of WirelessHART and share our first-hand experience in building a prototype for this specification. We describe several challenges we had to tackle during the implementation, such as the design of the timer, network wide synchronization, communication security, reliable mesh networking, and the central network manager. For each challenge, we provide a detailed analysis and propose our solution. Based on the prototype implementation, a simple WirelessHART network has been built for the purpose of demonstration. The demonstration network in turn validates our design. To the best of our knowledge, this is the first reported effort to build a WirelessHART protocol stack.

WirelessHART was released in September 2007 and is the first open wireless communication standard specifically designed for process control applications. As an optional part of the HART® Communication Protocol, WirelessHART is designed to the same standards for reliability and interoperability. To ensure the compliance and adherence to the high level of interoperability defined by the HART Communication Foundation (HCF), all WirelessHART devices must be thoroughly tested and registered with the HCF. In this paper, we present Wi-HTest, the test engine designed to exercise WirelessHART devices, thus facilitating compliance assessment. We discuss the detailed architecture of Wi-HTest and highlight several critical features like virtual devices and fault data injection.

WirelessHART is the first open wireless standard for the process control industry. Previously we demonstrated a three-node prototype network based on an early release of the protocol stack. In this demonstration we build a fully operational WirelessHART sensor network of multiple nodes. We show the creation of the network and the execution of process monitoring applications on the network. This new demonstration network serves as a proof of concept for the revised WirelessHART standard and as a platform for our future research and experiments.

Wireless sensor networks have been a very active research field in the past few years. However, most of extant research has focused on wireless sensing, such as environmental and habitat monitoring [6]. In this paper, we investigate the feasibility of applying wireless technologies in industrial real-time process control systems. We define a minimum set of assumptions about the underlying sensor networks in order to achieve realtime support for process control. These assumptions are necessary and practical from an industrial perspective. We formulate the modeling of a wireless process control configuration as a multi-processor scheduling problem. The resulting scheduling problem is solved by the scheduler synthesis tool MSP.RTL [7] to produce a valid configuration for deployment. The deployment, because of the way it is derived, will provide real-time wireless support for the controlled processes. Simulation results on data from real plant configurations show that this approach can also drastically reduce potential interferences between wireless transfers.

In a wireless sensor network, a sensor measures environmental data. It also relays data for other sensors. While sensing workload is the same among sensors, relaying workload differs. Sensors closer to the data sink carry more data traffic. This becomes more prominent as the network scales up. The drawback of this is that nodes in the network degrade unevenly and the network ages in a non-uniform way. This paper seeks the ways to deploy the network so that the workload is evenly distributed, thus the network overall behavior degrades in a smooth fashion. Assuming that the sensors should be evenly deployed within the monitored area, we look at the approach where a set of more powerful nodes are designated for data relaying. We look at the approach to deploy relaying nodes that are easy to implement in practice. In particular, we select sub-regions to deploy relaying nodes at calculated density. We propose a simple method where the density is simply based on the size of the area whose data is relayed by these nodes.

In a pure sensor network thousands of sensors are distributed over a large area. Sensor data is relayed from sensor node to node until it reaches the edge node, where it is then routed by wire to the host. In this paper we study the effect of data collection on the battery and buffer of a sensor node, and on the overall sensor network. We determine the relationship among battery life, sampling frequency, buffer size, etc. We claim that using identical sensors throughout a large scale sensor network may not achieve the best result. We suggest some guidelines for deploying a large scale sensor network. We then propose routing algorithms that are robust, truly distributed, and efficient in utilizing the sensor network.

A real-time task usually generates data. The study on real-time tasks either ignores this fact like most of the research do, or models data as execution time like when handling multimedia data. On the other hand, the network research community usually pays little attention to the data source other than assuming certain characteristics. There are many real world applications where data is not generated at a constant rate during task execution, and the average data rate is not the same among tasks. In this paper we study a new task model with data output as an explicit parameter. We analyze the data output of such task set. We shall derive the data source parameters assumed by network studies. Different scheduling policy results in different data output curve, we look at this in detail with simulations. Our work extends the real-time research to cover a new set of real world applications; it also complements the network study on data transmission.

The authors survey three approaches to extending the Hough transform that improve speed and reduce memory requirements. Two approaches center on the use of two-pass techniques to reduce dimensionality. One approach, specifically aimed at circle extraction, offers little more than a polar transformation. In the second approach, for ellipses, center coordinates and rotation are extracted in the first pass, and major and minor radii in the second. The final technique involves an iterative search procedure based on combining intersecting points between an approximation ellipse and its target and using a nonlinear least squares to evaluate the approximation. Each of these techniques requires less than 5% of the execution time of the equivalent Hough transform.>