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

IEEE 802.15.4-based wireless sensor-actuator networks (WSANs) have been quickly adopted by process industries in recent years because of their significant role in improving industrial efficiency and reducing operating cost. Battery-powered wireless modules can be used to easily and inexpensively retrofit existing sensors and actuators in industrial facilities without running cabling for communication and power. Wireless-enabled sensors, actuators, and controllers form a low-power multi-hop mesh network to exchange sensing data and control commands. Today, industrial WSANs are becoming tremendously larger and more complex than before. A large and complex mesh network is hard to manage and inelastic to change once the network is deployed. Besides, 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 delay, 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 paper presents our study on enabling the cross-technology communication (CTC) from LoRa to ZigBee (IEEE 802.15.4) using the energy emission of the LoRa radio in the 2.4 GHz band as the carrier to deliver information. Experimental results show that our CTC approach provides reliable communication from LoRa to ZigBee with the throughput of up to 576.80bps and the bit error rate (BER) of up to 5.23% in the 2.4 GHz band.

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, such as WirelessHART, ISA100, WIA-FA, and 6TiSCH, 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 (WSNs), 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 paper, we introduce ATRIA, 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.

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.

With the emergence of the Industrial Internet of Things (IIoT), process industries have started to adopt wireless sensor-actuator networks (WSANs) for control applications. It is crucial to achieve real-time communication in this emerging class of networks, and routing has significant impacts on end-to-end communication delays in WSANs. However, despite considerable research on real-time transmission scheduling and delay analysis for such networks, real-time routing remains an open question for WSANs. This paper presents a conflict-aware real-time routing approach for WSANs, leveraging a key observation that conflicts among transmissions involving a common field device can contribute significantly to communication delays in industrial WSANs, such as WirelessHART networks. By incorporating conflict delays into the routing decisions, conflict-aware real-time routing algorithms allow a WSAN to accommodate more real- time flows while meeting their deadlines. Both evaluations based on simulations and experiments on a physical WSAN testbed show that conflict-aware real-time routing can lead to as much as a three-fold improvement in the real-time capacity of WSANs.

Process industries are adopting wireless sensor-actuator networks (WSANs) as the communication infrastructure. WirelessHART is an open industrial standard for WSANs that have seen world-wide deployments. Real-time scheduling and delay analysis have been studied for WSAN extensively. End-to-end delay in WSANs highly depends on routing, which is still open problem. This paper presents the first real-time routing design for WSAN. We first discuss end-to-end delays of WSANs, then present our real-time routing design. We have implemented and experimented our routing designs on a wireless testbed of 69 nodes. Both experimental results and simulations show that our routing design can improve the real-time performance significantly.

Wireless Sensor-Actuator Network (WSAN) technology is gaining rapid adoption in process industries 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 make them ideal where battery lifetime and costs are important. Recent studies have shown that the selection of network parameters has a significant effect on the 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 the Parameter Selection and Adaptation FramEwork (P-SAFE) that optimally configures the network parameters based on the application Quality of Service (QoS) demand and adapts the configuration at runtime to consistently satisfy the dynamic requirements. We implement P-SAFE and evaluate it on three physical testbeds. Experimental results show our solution can significantly better meet the application QoS demand compared to the state of the art.

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.

Industrial automation is embracing wireless sensor-actuator networks (WSANs) as the communication technology for industrial Internet of Things. Due to the strict real-time and reliability constraints imposed by industrial applications, industrial WSAN standards such as WirelessHART employ centralized management to facilitate deterministic communication. However, a centralized management architecture faces significant challenges to adapt to changing wireless conditions. While earlier research on industrial WSANs has primarily focused on improving the performance of the data plane, there has been limited attention on the control plane, which plays a crucial role for sustaining the data plane performance in dynamic environments. This paper presents REACT, a reliable, efficient, and adaptive control plane for industrial WSANs. Specifically optimized for network adaptation, REACT significantly reduces the latency and energy cost of network reconfiguration, thereby improving the agility of WSANs in dynamic environments. REACT comprises (1) a Reconfiguration Planner employing flexible scheduling and routing algorithms and reactive update policies to reduce rescheduling cost, and (2) an Update Engine providing efficient and reliable mechanisms to report link failures and disseminate updated schedules. REACT has been implemented for a WirelessHART protocol stack. Evaluation results based on two testbeds demonstrate that REACT can reduce network reconfiguration latency by 60% at 50% of energy cost when compared to standard approaches.

Industrial automation has emerged as an important application of wireless sensor-actuator networks (WSANs). To meet stringent reliability requirements of industrial applications, industrial standards such as WirelessHART adopt Time Slotted Channel Hopping (TSCH) as its MAC protocol. Since every link hops through all the channels used in TSCH, a straightforward policy to ensure reliability is to retain a link in the network topology only if it is reliable in all channels used. However, this policy has surprising side effects. While using more channels may enhance reliability due to channel diversity, more channels may also reduce the number of links and route diversity in the network topology. We empirically analyze the impact of channel selection on network topology, routing, and scheduling on a 52-node WSAN testbed. We observe inherent tradeoff between channel diversity and route diversity in channel selection, where using an excessive number of channels may negatively impact routing and scheduling. We propose novel channel and link selection strategies to improve route diversity and network schedulability. Experimental results on two different testbeds show that our algorithms can drastically improve routing and scheduling of industrial WSANs.

Industrial Wireless Sensor-Actuator Networks (WSANs) enable Internet of Things (IoT) to be incorporated in industrial plants. The dynamics of industrial environments and stringent reliability requirements necessitate high degrees of fault tolerance. WirelessHART is an important industrial standard for WSANs that have seen world-wide deployments. WirelessHART employs graph routing to enhance network reliability through multiple paths. Since many industrial devices operate on batteries in harsh environments where changing batteries is prohibitively labor-intensive, WirelessHART networks need to achieve a long network lifetime. To meet industrial demand for long-term reliable communication, this paper studies the problem of maximizing network lifetime for WirelessHART networks under graph routing. We first formulate the network lifetime maximization problem and prove it is NP-hard. Then, we propose an optimal algorithm based on integer programming, a linear programming relaxation algorithm and a greedy heuristic algorithm to prolong the network lifetime of WirelessHART networks. Experiments in a physical testbed and simulations show our algorithms can improve the network lifetime by up to 60% while preserving the reliability benefits of graph routing.

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.

Wireless sensor-actuator networks enable an efficient and cost-effective approach for industrial sensing and control applications. To satisfy the real-time requirement of such applications, these networks adopt centralized scheduling algorithms to optimize the real-time performance based on global information. Existing centralized algorithms mostly focus on scheduling time-triggered flows. They cannot effectively schedule event-triggered flows due to the dynamics and unpredictability of events. In this paper, we propose three fundamental centralized algorithms that reserve as few resources as possible for event-triggered flows such that the real-time performance of time-triggered flows is not affected. We then analyze their advantages and disadvantages. Based on the analysis, we combine their advantages, including those in terms of their resource requirements, into a centralized algorithm. Finally, we conduct extensive simulations based on both real topologies and random topologies. The simulations indicate that for most test cases the schedulability of our combined algorithm is close to optimal solutions.

WirelessHART, as a robust and reliable wireless protocol, has been widely-used in industrial wireless sensoractuator networks. Its real-time performance has been extensively studied, but limited to the single criticality case. Many advanced applications have mixed-criticality communications, where different data flows come with different levels of importance or criticality. Hence, in this paper, we study the real-time mixedcriticality communication using WirelessHART protocol, and propose an end-to-end delay analysis approach based on fixed priority scheduling. To the best of our knowledge, this is the first work that introduces the concept of mixed-criticality into wireless sensor-actuator networks. Evaluation results show the effectiveness and efficacy of our approach.

Wireless Sensor-Actuator Networks (WSANs) technology is appealing for use in industrial IoT applications because it does not require wired infrastructure. Battery-powered wireless modules easily and inexpensively retrofit existing sensors and actuators in industrial facilities without running cabling for communication and power. 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 industrial facilities. Today we are facing the 4th 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 a 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 Distributed Graph routing and autonomous Scheduling (DiGS) solution that allows the field devices to compute their own graph routes and transmission schedules. Experimental results from two physical testbeds and a simulation study show our approaches can significantly improve the network reliability, latency, and energy efficiency under dynamics.

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.