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Industrial wireless sensor networks (IWSNs) are required to provide highly reliable and real-time transmission. Moreover, for connected K-neighborhood (CKN) sleep scheduling-based duty-cycled IWSNs in which the network lifetime of IWSNs can be prolonged, the two-phase geographic greedy forwarding (TPGF) geographic routing algorithm has attracted attention due to its unique transmission features: multi path, shortest path, and hole bypassing. However, the performance of TPGF in CKN-based duty-cycled IWSNs with radio irregularity is not well investigated in the literature. In this paper, we first evaluate the impact of radio irregularity on CKN-based duty-cycled IWSNs. Furthermore, we investigate the routing performance of TPGF in CKN-based duty-cycled IWSNs with radio irregularity, in terms of the number of explored routing paths as well as the lengths of the average and shortest routing paths. Particularly, we establish the upper bound on the number of explored routing paths. The upper bound is slightly relaxed with radio irregularity compared with without radio irregularity; however, it is bounded by the number of average 1-hop neighbors in always-on IWSNs. With extensive simulations, we observe that the cross-layer optimized version of TPGF (i.e., TPFGPlus) finds reliable transmission paths with low end-to-end delay, even in CKN-based duty-cycled IWSNs with radio irregularity.

Although mature industrial wireless sensor network applications increasingly require low-power operations, deterministic communications, and end-to-end reliability, it is very difficult to achieve these goals because of link burstiness and interference. In this paper, we propose a novel link quality estimation mechanism named the burstiness distribution metric, which uses the distribution of burstiness in the links to deal with variations in wireless link quality. First, we estimated the quality of the link at the receiver node by counting the number of consecutive packets lost in each link. Based on that, we created a burstiness distribution list and estimated the number of transmissions. Our simulation in the Cooja simulator from Contiki-NG showed that our proposal can be used in scheduling as an input metric to calculate the number of transmissions in order to achieve a reliability target in industrial wireless sensor networks.

Wireless networked control systems (WNCSs) must ensure that control systems are stable, robust and capable of minimizing the effects of disturbances. Due to the need for a stable and secure WNCS, critical wireless network variables must be taken into account in the design. As wireless networks are composed of several links, factors that indicate the performances of these links can be used to evaluate the communication system in the WNCS. This work presents a wireless network control system composed of ISA 100.11a sensors, a network manager, a controller and a wired actuator. The system controls the liquid level in the tank of the coupled tank system. In order to assess the influence of the sensor link failure on the control loop, the controller calculates the link stability and chooses an alternative link in case of instability in the current link. Preliminary tests of WNCS performance were performed to determine the minimum stability value of the link that generates an error in the control loop. Finally, the tests of the control system based on link stability obtained excellent results. Even with disturbances in the network links, the control system error remained below the threshold.

Time synchronization is an essential issue in industrial wireless sensor networks (IWSNs). It assists perfect coordinated communications among the sensor nodes to preserve battery power. Generally, time synchronization in IWSNs has two major aspects of energy consumption and accuracy. In the literature, the energy consumption has not received much attention in contrast to the accuracy. In this paper, focusing on the energy consumption aspect, we introduce an energy-efficient reference node selection (EERS) algorithm for time synchronization in IWSNs. It selects and schedules a minimal sequence of connected reference nodes that are responsible for spreading timing messages. EERS achieves energy consumption synchronization by reducing the number of transmitted messages among the sensor nodes. To evaluate the performance of EERS, we conducted extensive experiments with Arduino Nano RF sensors and revealed that EERS achieves considerably fewer messages than previous techniques, robust time synchronization (R-Sync), fast scheduling and accurate drift compensation for time synchronization (FADS), and low power scheduling for time synchronization protocols (LPSS). In addition, simulation results for a large sensor network of 450 nodes demonstrate that EERS reduces the whole number of transmitted messages by 52%, 30%, and 13% compared to R-Sync, FADS, and LPSS, respectively.

When an industrial wireless sensor network (WSN) is seriously disturbed and intentionally attacked, sometimes it fails easily, even leading to the paralysis of the entire industrial wireless network. In order to improve the invulnerability of networks, in this paper, the scale-free network in complex networks is taken as the research object, and the industrial WSN with scale-free characteristics is modeled. Based on the advantages of the fireworks algorithm, such as strong searching ability and diversity of population, a so-called fireworks and particle swarm optimization (FW-PSO) algorithm is proposed, which can improve the global search ability and convergence speed effectively. The proposed FW-PSO algorithm is used to optimize the network topology and form a network with the largest natural connectivity, which can effectively promote the ability of network to resist the cascade failure problem. The dynamic invulnerability of the optimized network under highest-degree (HD) attack and lowest-degree (LD) attack strategies, as well as the static invulnerability under random attack, were evaluated respectively. Simulation experiments show that the industrial WSN optimized by FW-PSO can significantly improve the performance of the dynamic and static invulnerabilities compared with the initial network and the networks optimized by the other two existing algorithms.

This paper presents on the results of radiation studies for three commonly used wireless sensor nodes based on the following protocols: ZigBee, WirelessHART, ISA 100.11a, and network devices built with commercial off-the-shelf (COTS) components. The level of radiation considered is at par with that experienced at Fukushima Daiichi Nuclear Power Plant after the accident. An experimental setup is developed to monitor behaviors of each wireless device and network real-time under the 60Co gamma radiator at The Ohio State University Nuclear Reactor Lab (OSU-NRL). The experimental results have indicated that the performance of the communication channels and wireless signal parameters do not degrade significant under such radiation. However, all the tested devices and networks can only survive for several hours under the high dose rate condition (20 K Rad/h). The results of these experimental studies have provided useful references to those who design and manufacture COTS-based wireless monitoring systems for use in high level radiation environments.

Relaying with packet aggregation has been recognized as an effective strategy to improve both reliability and energy efficiency for industrial wireless sensor networks. However, existing analyses have been largely based on the assumption of reliable feedback, which are not suitable for many practical networks, where feedback messages are transmitted with equal rate as data messages. This letter proposes a selection cooperation protocol using packet aggregation with equal rate feedback. Four aggregation schemes are presented for centralized and distributed scenarios, and a diffusion method is investigated to further increase potential relay number. Simulation results demonstrate the performance of the proposed aggregation schemes. [ABSTRACT FROM AUTHOR]

Industrial wireless sensor networks have been widely deployed in many industrial systems. The main communication paradigm of such systems, known as convergecast, is to converge sensing data to a centralized manager. The rapid and reliable data convergecast is essential to the industrial production. Multiple radio interfaces on a network device and convergecast scheduling algorithms can effectively reduce convergecast delay. Existing works confine to the convergecast based on linear- and tree-based routing. Compared to the two routing schemes, graph routing is more reliable. Although the graph routing gains more popularity in industrial networks due to its better reliability, few works have addressed its temporality performance. On the other hand, the number of radio interfaces also impacts on the convergecast delay. In this paper, we present a holistic framework to solve how to use multiple radio interfaces to converge data. First, we propose a convergecast scheduling algorithm for industrial wireless sensor networks with multiple radio interfaces. Second, based on our proposed scheduling algorithm, we propose an optimal algorithm and a fast heuristic algorithm to minimize the number of radio interfaces under the temporality constraint of industrial production. Evaluations show that all our algorithms perform closely to the optimal solution. [ABSTRACT FROM AUTHOR]

The IEC standard WIA-PA is a communication protocol for industrial wireless sensor networks. Its special features, including a hierarchical topology, hybrid centralized-distributed management and packet aggregation make it suitable for large-scale industrial wireless sensor networks. Industrial systems place large real-time requirements on wireless sensor networks. However, the WIA-PA standard does not specify the transmission methods, which are vital to the real-time performance of wireless networks, and little work has been done to address this problem. In this article, we propose a real-time aggregation scheduling method for WIA-PA networks. First, to satisfy the real-time constraints on dataflows, we propose a method that combines the real-time theory with the classical bin-packing method to aggregate original packets into the minimum number of aggregated packets. The simulation results indicate that our method outperforms the traditional bin-packing method, aggregating up to 35% fewer packets, and improves the real-time performance by up to 10%. Second, to make it possible to solve the scheduling problem of WIA-PA networks using the classical scheduling algorithms, we transform the ragged time slots of WIA-PA networks to a universal model. In the simulation, a large number of WIA-PA networks are randomly generated to evaluate the performances of several real-time scheduling algorithms. By comparing the results, we obtain that the earliest deadline first real-time scheduling algorithm is the preferred method for WIA-PA networks. [ABSTRACT FROM AUTHOR]

Time synchronization is critical for wireless sensors networks in industrial automation, e.g., event detection and process control of industrial plants and equipment need a common time reference. However, cyber-physical attacks are enormous threats causing synchronization protocols to fail. This paper studies the algorithm design and analysis in secure time synchronization for resource-constrained industrial wireless sensor networks under Sybil attacks, which cannot be well addressed by existing methods. A node-identification-based secure time synchronization (NiSTS) protocol is proposed. The main idea of this protocol is to utilize the timestamp correlation among different nodes and the uniqueness of a node’s clock skew to detect invalid information rather than isolating suspicious nodes. In the detection process, each node takes the relative skew with respect to its public neighbor as the basis to determine whether the information is reliable and to filter invalid information. The information filtering mechanism renders NiSTS resistant to Sybil attacks and message manipulation attacks. As a completely distributed protocol, NiSTS is not sensitive to the number of Sybil attackers. Extensive simulations were conducted to demonstrate the efficiency of NiSTS and compare it with existing protocols. [ABSTRACT FROM AUTHOR]

In the mobile industrial human–machine interaction (HMI), to establish the data connection, the engineer has to manually select the target machine from a long list, which may lead to wrong connection and waste of time. We observe that the engineer should face to the machine during the interaction to ensure that the machine works accurately, and this characteristic makes the proximity estimation algorithm suitable to simplify the data connection. However, due to the densely deployed machines, the existing algorithms cannot provide sufficient accuracy with limited latency. In this paper, we implement a testbed to evaluate the performance in the mobile industrial HMI. Based on the experimental results, we propose the definition of received signal strength indicator (RSSI) difference and then use it to design the face-to-machine proximity estimation (FaceME) algorithm. The experimental results prove that FaceME can provide guaranteed estimation accuracy and low-time complexity. [ABSTRACT FROM AUTHOR]

Industrial wireless sensor networks (IWSNs) designed for mission- and time-critical applications require timely and deterministic data delivery within stringent deadline bounds. Exceeding delay limits for such applications can lead to system malfunction or ultimately dangerous situations that can threaten human safety. In this paper, we propose Slot Stealing Medium Access Control (SS-MAC), an efficient SS-MAC protocol to guarantee predictable and timely channel access for time-critical data in IWSNs. In the proposed SS-MAC, aperiodic time-critical traffic opportunistically steals time slots assigned to periodic non-critical traffic. Additionally, a dynamic deadline-based scheduling is introduced to provide guaranteed channel access in emergency and event-based situations, where multiple sensor nodes are triggered simultaneously to transmit time-critical data to the controller. The proposed protocol is evaluated mathematically to provide the worst-case delay bound for the time-critical traffic. Performance comparisons are carried out between the proposed SS-MAC and WirelessHART standard and they show that, for the time-critical traffic, the proposed SS-MAC can achieve, at least, a reduction of almost 30% in the worst-case delay with a significant channel utilization efficiency. [ABSTRACT FROM PUBLISHER]

Wireless Sensor Networks is a promising technology for industrial monitoring and process control. In industry the sensory measures should be delivered to control room in predefined deadline time. The reliable delivery of sensory measure degrades as the focus shift from wired domain to wireless domain. This happens due to unreliability of sensor node and communication link. Therefore, the adverse industrial environment condition posed great stress towards designing of an efficient and effective routing protocol that can ensure the quality of service by reliable and timeliness delivery of real-time data. This paper presents a new geographical routing protocol that works on the basis of two-hop neighbor information. This improves end-to-end packet delivery by minimizing the path setup and recovery latency to ensure the reliability and timeliness. It selects the reliable relay node by mapping packet deadline time to link velocity in such a way that the smaller deadline time packets follow the shorter path over the high speed, reliable links and larger deadline time packets follow path over energy efficient nodes. This process enhances the network life and maintains the shorter path for time critical data routing. This real-time data routing suffers when a forwarding node fails to access the potential relay node. Here, the transmission energy regulation mechanism support to accessing the potential relay node for improving the reliability and timeliness data delivery. The simulation results validate the claim that the proposed routing protocol achieves significant improvement in end-to-end deadline packet delivery ratio with the higher energy efficiency. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are widely applied in industrial application with the rapid development of Industry 4.0. Combining with centralized cloud platform, the enormous computational power is provided for data analysis, such as strategy control and policy making. However, the data analysis and mining will bring the issue of privacy leakage since sensors will collect varieties of data including sensitive location information of monitored objects. Differential privacy is a novel technique that can prevent compromising single record benefits. Geospatial data can be indexed by a tree structure; however, existing differentially private release methods pay no attention to the concrete analysis about the partition granularity of data domains. Based on the overall analysis of noise error and non-uniformity error, this paper proposes a data domain partitioning model, which is more accurate to choose the grid size. A uniform grid release method is put forward based on this model. In order to further reduce the errors, similar cells are merged, and then noise is added into the merged cells. Results show that our method significantly improves the query accuracy compared with other existing methods. [ABSTRACT FROM AUTHOR]

Industrial wireless sensor networks can help improve the efficiency, reconfigurability and flexibility of future factories, and facilitate the introduction of new applications. Industrial applications are generally characterized with strict reliability and latency requirements. The capacity to meet such requirements is highly dependent on an efficient utilization of communication links. Such efficient utilization will become even more critical as the number of deployed sensors and traffic in factories increase. In this context, this paper presents a novel link scheduling scheme for industrial wireless sensor networks that uses shared links among nodes that are part of the same path or multi-hop route. The transmission of a message along a route acts as a virtual token to identify which node should use the shared links at each point in time. This study demonstrates that the proposed link scheduling scheme can significantly improve the reliability, latency and efficiency of industrial wireless sensor networks. The proposed link scheduling scheme is here applied to industrial wireless sensor networks, but it can be used in other centralized TDMA-based multi-hop wireless networks. [ABSTRACT FROM AUTHOR]

This paper proposes a real-time and energy aware routing protocol for industrial wireless sensor networks, called RTEA. Two-hop neighborhood information routing is adopted from THVR routing protocol, however our routing protocol has low control packet overhead and differentiates packets based on their deadlines. The packet deadline is updated in each hop without using globally synchronized clocks. In addition to velocity, the distance to the sink is considered for reducing the number of relaying hops. Also, the delay between two one-hop neighbors is estimated by a new mechanism which considers the time that packets spend in each node beside the link delay. Simulation results show that RTEA can improve the performance in terms of delivery ratio and energy consumption. [ABSTRACT FROM AUTHOR]

Adaptive mechanisms, such as dynamic channel allocation or adaptive routing, are used to deal with the variations in the link quality of Wireless Sensor Networks (WSN). In both cases, the first step is to estimate the link quality, so that the network nodes can decide if a channel or route change is needed. This paper proposes a Link Quality Estimator (LQE) for Industrial WSN, and a new type of node, the LQE node, that estimates the link quality in real-time, using the Received Signal Strength Indication (RSSI), and information obtained from received data packets. The proposed LQE is capable of capturing the effects of multipath, interference, and link asymmetry. Experiments were performed in a real industrial environment using IEEE 802.15.4 radios, and models were developed to allow the use of RSSI samples to proper estimate the link quality. A comparison was performed with a state-of-the-art LQE, the Opt-FLQE, and the results showed that the proposed estimator is more accurate and reactive for the type of environment in study. Different from other LQEs in literature, in the proposed LQE the sensor nodes do not need to send broadcast probe packets. Besides, using the LQE node, the other nodes of the WSN do not need to stop their operation to monitor the link quality. [ABSTRACT FROM AUTHOR]

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs' demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays. [ABSTRACT FROM AUTHOR]

Recently, the United Nations voted to grant a frequency band for wireless avionics intra-communications (WAICs) to replace the heavy and expensive cables used in aircraft with wireless systems. However, WAICs require extremely low failure probability for the flight certification of the safety-critical avionics applications. Existing industrial wireless networks are possible candidate technologies, since they are designed to meet the high reliability requirement of industrial automation within a harsh environment surrounded by metals. This letter provides a theoretical framework to compare the performance of representative industrial wireless networks against the system requirements of the flight certification. A mathematical model is proposed to evaluate the considered protocols in terms of the deadline missing probability per flight hour. Furthermore, the model is used to derive the maximum allowable packet loss probability while guaranteeing the flight certification. [ABSTRACT FROM PUBLISHER]

Process parameter estimation, to a large extent, determines the industrial production quality. However, limited sensors can be deployed in a traditional wired manner, which results in poor process parameter estimation in hostile environments. Industrial wireless sensor networks (IWSNs) are techniques that enrich sampling points by flexible sensor deployment and then purify the target by collaborative signal denoising. In this paper, the process industry scenario is concerned, where the workpiece is transferred on the belt and the parameter estimate is required before entering into the next process stage. To this end, a consensus-based sequential estimation (CSE) framework is proposed which utilizes the co-design of IWSN and parameter state estimation. First, a group-based network deployment strategy, together with a TDMA (Time division multiple access)-based scheduling scheme is provided to track and sample the moving workpiece. Then, by matching to the tailored IWSN, the sequential estimation algorithm, which is based on the consensus-based Kalman estimation, is developed, and the optimal estimator that minimizes the mean-square error (MSE) is derived under the uncertain wireless communications. Finally, a case study on temperature estimation during the hot milling process is provided. The results show that the estimation error can be reduced to less than 3 ∘ C within a limited time period, although the measurement error can be more than 100 ∘ C in existing systems with a single-point temperature sensor.

Wireless sensor networks (WSNs) are widely applied in industrial application with the rapid development of Industry 4.0. Combining with centralized cloud platform, the enormous computational power is provided for data analysis, such as strategy control and policy making. However, the data analysis and mining will bring the issue of privacy leakage since sensors will collect varieties of data including sensitive location information of monitored objects. Differential privacy is a novel technique that can prevent compromising single record benefits. Geospatial data can be indexed by a tree structure; however, existing differentially private release methods pay no attention to the concrete analysis about the partition granularity of data domains. Based on the overall analysis of noise error and non-uniformity error, this paper proposes a data domain partitioning model, which is more accurate to choose the grid size. A uniform grid release method is put forward based on this model. In order to further reduce the errors, similar cells are merged, and then noise is added into the merged cells. Results show that our method significantly improves the query accuracy compared with other existing methods.

Focusing on the leak-points in petrochemical industries, this paper discusses the key factors (i.e., equipment temperature, gas pressure, and diffusion rate) in petrochemical industries. Data from sensors of petrochemical industries need to be timely operated because of time sensitivity and it is hard to achieve associated information from sensors located in production sites. To this end, we propose a three-level framework based on improved back propagation (TLBP). The real-time data streams are processed according to the arriving time in input layer. At the same time, a neuron-optimizing solution is introduced in learning process to deal with redundant and invalid neurons, thereby accelerating the response speed of learning and reducing the prediction time. Finally, we propose an improved mechanism of the multidimensional learning factor to lower the learning error and higher convergence rate. Meanwhile, to fulfill the distributed prediction on leak-points, we see one three-level data-processing unit as a logic machine with multiple operators. Using the assignment scheduling, the general scheduling problem is split into the common subproblem of every operator and the system overhead is reduced. With the processed data we can obtain the relative location or diffusion radius of leak-points, as well as the area of leak-points. Simulation results show that the TLBP performs better than related algorithms in different metrics. Besides, the adaptability of TLBP is verified in leak-points prediction of petrochemical equipment from the processed data. [ABSTRACT FROM PUBLISHER]

Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones. [ABSTRACT FROM AUTHOR]

Recent developments in the field of micro‐electro mechanical systems and wireless sensor networks made revolutionary changes in industrial automation and process control. However, harsh and complex industrial environment pose great challenges toward real‐time and reliable wireless communication. This necessitates a routing protocol that fulfils the industrial current real‐time, reliable routing needs and opens the door for new applications that may arise in future. This study presents critical data reliable routing protocol for industrial real‐time applications. That dynamically selects the reliable relay node by considering the data type, deadline time along with the recent parameters of the network. These parameters are selected in such a way that the critical data forwarding follow shorter path over speedy, reliable links and non‐critical data forwarding follow the path over energy efficient nodes. In this way, the relay node selection process balances the network load that the shorter path remains available for the shorter deadline‐time critical data. The results show improvement in timeliness data delivery along enhanced network life. As far as a node failure is concerned, the forwarding node fails to access potential relay node. Therefore, following transmission energy regulation mechanism optimises this problem with enhancing timeliness data delivery. [ABSTRACT FROM AUTHOR]

Industrial wireless sensor networks (IWSNs) are advancing to a form of active networks called industrial wireless active sensor networks (IWASNs) with reprogrammable sensor nodes, and thus require a method to check the integrity of software in sensor nodes. Regarding energy efficiency, however, previous methods did not take into account the scalability of IWASNs and thus performed inefficiently. In this paper, we propose FlexiCast, which presents a novel energy-efficient method to check the integrity of software objects. Sensor nodes can efficiently detect a modification in software objects sent by a base station or stored in neighboring nodes through authenticated fingerprints and network-wide attestation. Our analysis shows that FlexiCast can reduce energy consumption by 71% for both updating software objects and checking modifications regarding more critical attacks. [ABSTRACT FROM PUBLISHER]

Industrial wireless sensor networks (IWSNs) have to contend with environments that are usually harsh and time-varying. Industrial wireless technology, such as WirelessHART and ISA 100.11a, also operates in a frequency spectrum utilized by many other wireless technologies. With wireless applications rapidly growing, it is possible that multiple heterogeneous wireless systems would need to operate in overlapping spatiotemporal regions. Interference such as noise or other wireless devices affects connectivity and reduces communication link quality. This negatively affects reliability and latency, which are core requirements of industrial communication. Building wireless networks that are resistant to noise in industrial environments and coexisting with competing wireless devices in an increasingly crowded frequency spectrum is challenging. To meet these challenges, we need to consider the benefits that approaches finding success in other application areas can offer industrial communication. Cognitive radio (CR) methods offer a potential solution to improve resistance of IWSNs to interference. Integrating CR principles into the lower layers of IWSNs can enable devices to detect and avoid interference, and potentially opens the possibility of utilizing free radio spectrum for additional communication channels. This improves resistance to noise and increases redundancy in terms of channels per network node or adding additional nodes. In this paper, we summarize CR methods relevant to industrial applications, covering CR architecture, spectrum access and interference management, spectrum sensing, dynamic spectrum access (DSA), game theory, and CR network (CRN) security. [ABSTRACT FROM PUBLISHER]

The widespread adoption of wireless systems for industrial automation calls for the development of efficient tools for virtual planning of network deployments similarly as done for conventional Fieldbus and wired systems. In industrial sites the radio signal propagation is subject to blockage due to highly dense metallic structures. Network planning should therefore account for the number and the density of the 3D obstructions surrounding each link. In this paper we address the problem of wireless node deployment in wireless industrial networks, with special focus on WirelessHART IEC 62591 and ISA SP100 IEC 62734 standards. The goal is to optimize the network connectivity and develop an effective tool that can work in complex industrial sites characterized by severe obstructions. The proposed node deployment approach is validated through a case study in an oil refinery environment. It includes an ad-hoc simulation environment (RFSim tool) that implements the proposed network planning approach using 2D models of the plant, providing connectivity information based on user-defined deployment configurations. Simulation results obtained using the proposed simulation environment were validated by on-site measurements. [ABSTRACT FROM AUTHOR]

The reliability of wireless sensor networks (WSNs) in industrial applications can be thwarted due to multipath fading, noise generated by industrial equipment or heavy machinery and particularly by the interference generated from other wireless devices operating in the same spectrum band. Recently, cognitive WSNs (CWSNs) were proposed to improve the performance and reliability of WSNs in highly interfered and noisy environments. In this class of WSN, the nodes are spectrum aware, that is, they monitor the radio spectrum to find channels available for data transmission and dynamically assign and reassign nodes tolow-interference conditionchannels. In this work, we present the implementation of a channel assignment algorithm in a field-programmable gate array, which dynamically assigns channels to sensor nodes based on the interference and noise levels experimented in the network. From the results obtained from the performance evaluation of the CWSN when the channel assignment algorithm is considered, it is possible to identify how many channels should be available in the network in order to achieve a desired percentage of successful transmissions, subject to constraints on the signal-to-interference plus noise ratio on each active link. [ABSTRACT FROM PUBLISHER]

Industrial wireless sensor networks (IWSNs) have the potential to contribute significantly in areas such as cable replacement, mobility, flexibility, and cost reduction. Nevertheless, the industrial environment that the IWSNs operate in is very challenging because of dust, heat, water, electromagnetic interference, and interference from other wireless devices, which make it difficult for current IWSNs to guarantee reliable real-time communication. In this paper, we present a novel method based on the segmented slot assignment, fast slot competition, and free node concept that will improve the reliability and real-time communication significantly so that more advanced applications can be enabled. The main purpose of the algorithms is to improve the retransmission efficiency for time-division-multiple-access-based multihop IWSNs by using limited shared slot resources more efficiently. More importantly, the proposed algorithms support efficient slot rescheduling caused by link or node failure. We evaluate the proposed methods by using simulations and a real implementation targeting monitoring of welder machines. Our obtained results show that the proposed method outperforms the first published and most widely used IWSN standard called WirelessHART. [ABSTRACT FROM PUBLISHER]

SUMMARY As considerable progress has been made in wireless sensor networks (WSNs), we can expect that sensor nodes will be applied in industrial applications. Most available techniques for WSNs can be transplanted to industrial wireless sensor networks (IWSNs). However, there are new requirements of quality of service (QoS), that is, real-time routing, energy efficiency, and transmission reliability, which are three main performance indices of routing design for IWSNs. As one-hop neighborhood information is often inadequate to data routing in IWSNs, it is difficult to use the conventional routing methods. In the paper, we propose the routing strategy by taking the real-time routing performance, transmission reliability, and energy efficiency (TREE, triple R and double E) into considerations. For that, each sensor node should improve the capability of search range in the phase of data route discovery. Because of the increase of available information in the enlarged search range, sensor node can select more suitable relay node per hop. The real-time data routes with lower energy cost and better transmission reliability will be used in our proposed routing guideline. By comparing with other routing methods through extensive experimental results, our distributed routing proposal can guarantee the diversified QoS requirements in industrial applications. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Wide-area situational awareness for critical infrastructure protection has become a topic of interest in recent years. As part of this interest, we propose in this paper a smart mechanism to: control real states of the observed infrastructure from anywhere and at any time, respond to emergency situations and assess the degree of accuracy of the entire control system. Particularly, the mechanism is based on a hierarchical configuration of sensors for control, the ISA100.11a standard for prioritization and alarm management, and the F-Measure technique to study the level of accuracy of a sensor inside a neighborhood. [Copyright &y& Elsevier]