Industrial Wireless Research Articles

Frame-based randomized scheduling of packets with random-deadlines for multi-flow wireless networks

The use of wireless communications in industrial applications has motivated various advances in manufacturing automation by allowing more flexibility in installing wireless sensors and actuators than their wired counterparts. The main challenge in industrial wireless deployment is the strict timing and reliability requirements in these systems. Industrial wireless networks are commonly characterized by strict packet deadlines. As a result, Time Division Multiple Access (TDMA) protocols have been widely exploited in various technologies due to their ease of implementation and packet collision avoidance. Moreover, the use of frame-based protocols is motivated by the need for short processing times at the edge nodes of the network. In this work, we consider the problem of scheduling multiple data flows over a wireless network operating in an industrial environment. These flows are characterized by random strict deadlines for each packet following a given probability distribution. Each of these flows may represent the data coming from a sensor to the controller or the control commands from the controller to an actuator. A randomized frame-based scheduling scheme is analyzed where each time slot in the frame is assigned to a data flow randomly.

Design, analysis and implementation of a time-bounded spectrum handoff algorithm for real-time industrial wireless sensor and actuator networks

Industrial control applications require real-time communication systems with time-critical and safety-critical features, as well as the ability to operate in harsh propagation environments. This means that data communications need to be bounded both in time and reliability domains, while dealing with severe interference coming from other wireless communication systems, including jammers, and with signal degradation phenomena such as delay spread, deep fading or Doppler spread. The present work proposes a spectrum handoff (i.e. channel switching) mechanism for Industrial Wireless Sensor and Actuator Networks (IWSAN) which is capable of detecting interferences and hopping to another channel within a given time bound. This is possible because the spectrum handoff strategy is capable of detecting interference in the MAC layer with the high requirements demanded by real-time IWSAN applications in terms of time and reliability. A theoretical analysis has first been provided using Network Calculus, which determines the delay bounds, and simulations in OPNET have been done afterwards in order to validate the theoretical results, taking into account several industrial environments (e.g. lognormal shadowing, Rice and Rayleigh fading and interference). Furthermore, the proposed communication system, based on the IEEE 802.11a/g physical layer, has been implemented in a FPGA, and simulations in OPNET network simulator and measurements on real hardware have been carried out in order to characterize its performance. The obtained results prove the capability of the proposed spectrum handoff mechanism to guarantee bounded delays and reliable operation in harsh propagation environments with interference, what makes it a suitable candidate for replacing wired communication systems in industrial environments.

Consensus-Based Sequential Estimation of Process Parameters via Industrial Wireless Sensor Networks.

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 within a limited time period, although the measurement error can be more than in existing systems with a single-point temperature sensor.

From Best Effort to Deterministic Packet Delivery for Wireless Industrial IoT Networks

Wireless industrial networks require reliable and deterministic communication. Determinism implies that there must be a guarantee that each data packet will be delivered within a bounded delay. Moreover, it must ensure that the potential congestion or interference will not impact the predictable properties of the network. In 2016, IEEE 802.15.4 time-slotted channel hopping (TSCH) emerged as an alternative medium access control to the industrial standards such as WirelessHART and ISA100.11a. However, TSCH is based on traditional collision detection and retransmission, and cannot guarantee reliable delivery within a given time. This paper proposes LeapFrog Collaboration (LFC) to provide deterministic and reliable communication over a routing protocol (RPL) based network. LFC is a novel multipath routing algorithm that takes advantage of route diversity by duplicating the data flow onto an alternate path. Simulations and analytical results demonstrate that LFC significantly outperforms the single-path retransmission-based approach of RPL $+$ TSCH and the state-of-the-art LinkPeek solution.

A Review on Skin Cancer Data Using Image Processing

The wireless industry is going very fast nowadays. We can easily see the evolution from 2G to 3G and now advance to the 4G and 5G network. Before wireless networks, wired networks were commonly used in every field. But there were some disadvantages regarding mobility, quality of service and connectivity. Wired network bounded the region of the working area for the internet and it requires multiple wires to connect computer from one device to another. While on the other hand wireless network is an open source for everyone to use the internet. There is no limitation of the region and no issue regarding connectivity because data is transfer through signal which includes frequency in the form of waves. But there are also some disadvantages of wireless network regarding cost, speed, coverage, bandwidth etc. If we talk about the better network so it depends on the situation and problem.

A Survey on Wired and Wireless Network

The wireless industry is going very fast nowadays. We can easily see the evolution from 2G to 3G and now advance to the 4G and 5G network. Before wireless networks, wired networks were commonly used in every field. But there were some disadvantages regarding mobility, quality of service and connectivity. Wired network bounded the region of the working area for the internet and it requires multiple wires to connect computer from one device to another. While on the other hand wireless network is an open source for everyone to use the internet. There is no limitation of the region and no issue regarding connectivity because data is transfer through signal which includes frequency in the form of waves. But there are also some disadvantages of wireless network regarding cost, speed,coverage, bandwidth etc. If we talk about the better network so it depends on the situation and problem.

Data fusion of wireless sensor network for prognosis and diagnosis of mechanical systems

With the promotion of the latest technologies and the new requirement of humanitarian, the wireless multi-sensor system is applied broadly. This paper studies the data fusion of the industrial wireless sensor networks (IWSNs), in order to acquire more thoughtful data for the prognosis and diagnosis of the monitored device. These authors propose a combination of back propagation neural network (BP NN) and Wavelet Packet algorithm for data fusion. This proposed algorithm is based on each cluster head, which is modelled with a three layers NN. A case study using the ball bearing test data, which is from the Bearing Data Center of the Case Western Reserve University, and to verify the effectiveness of the proposed algorithm. With MATLAB 2016b version, the raw data feature is extracted by the Wavelet Packet and the feature fusion is based on BP NN at sink node. The simulation results show that the proposed algorithm is effective in fault diagnosis of wind turbine.

The Effects of Rapid Technological Change on Regulatory Policies in the Communications Sector

Predicting what future changes in technology may occur is often an impossible endeavor. Designing effective regulatory policies around changing technologies is even more difficult, as it requires understanding how those changes may alter market conditions that often render such policies obsolete or even counterproductive. This report draws on a sizable history of past regulatory and antitrust interventions whose results demonstrate that: • In a fast-changing industry, it is often very difficult to predict developments that dramatically change the market. • In industries characterized by rapid technological change, regulation often leads to counterproductive constraints on firms. Moreover, history shows that such counterproductive regulations are often hard to lift and stay in place for a long time. • The wireless industry is in the midst of a major technological change, a move to 5G, and competitors have already successfully entered with new business models (cable companies, DISH, and others, including Google and other tech companies). As a result, predicting future market conditions is particularly difficult. • Therefore, at this time the regulators should be particularly cautious intervening.

Packet Aggregation Real-Time Scheduling for Large-Scale WIA-PA Industrial Wireless Sensor Networks

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.

On the Performance of Cooperative Transmission Schemes in Industrial Wireless Sensor Networks

This paper studies the performance of six transmission schemes, namely single-hop, multihop, selective decode-and-forward, amplify-and-forward, incremental decode-and-forward (IDF), and incremental amplify-and-forward (IAF) schemes. For a fair comparison, these schemes are constrained in terms of maximum outage probability and end-to-end throughput. In this paper, we investigate the impact of propagation channel conditions including both line-of-sight and non-line-of-sight environments by exploiting Nakagami-m fading channel. Our simulation results show that, by utilizing a return channel, the IDF and IAF cooperative schemes achieve better performance than the other schemes in most cases.

Measuring Two-Factor Authentication Schemes for Real-Time Data Access in Industrial Wireless Sensor Networks

Dozens of two-factor authentication schemes have been proposed to secure real-time data access in industrial wireless sensor networks (WSNs). However, more often than not, the protocol designers advocate the merits of their scheme, but do not reveal (or unconsciously ignoring) the facets on which their scheme performs poorly. Such lack of an objective, comprehensive measurement leads to the unsatisfactory “break-fix-break-fix” cycle in this research area. In this paper, we make an attempt toward breaking this undesirable cycle by proposing a systematical evaluation framework for schemes to be assessed objectively, revisiting two foremost schemes proposed by Wu et al. (2017) and Srinivas et al. (2017) to reveal the challenges and difficulties in designing a sound scheme, and conducting a measurement of 44 representative schemes under our evaluation framework, thereby providing the missing evaluation for two-factor schemes in industrial WSNs. This work would help increase awareness of current measurement issues and improve the scientific process in our field.

Channel List Selection Based on Quality Prediction in WirelessHART Networks

WirelessHART is one of the most widely used technologies in industrial wireless networks. However, its performance is highly influenced by the quality of wireless channels. To improve the reliability of wireless communications, WirelessHART employs channel blacklisting and channel hopping mechanisms, which highlights the importance of channel assessment. Traditional methods generally resort to packet reception ratio (PRR) of the previous time slot to assess and allocate channels, but this is not accurate. In this paper, we propose a learning-based framework for predicting the PRR, and on the basis of the predicted PRR, we develop a heuristic channel selection algorithm to confirm the channel list, which takes into account the balance of channel diversity and route diversity. Simulation results demonstrate that our algorithm outperforms existing ones in terms of achieved reliability.

Bio‐inspired routing protocol for WSN‐based smart grid applications in the context of Industry 4.0

AbstractRecently, the advences of Industry 4.0 have paved the way for a systematical deployment of the smart grid (SG) to manage continuously growing energy demand of the 21st century. This even allows the fourth stage of the industrial revolution in the power sector, which is known as the smart grid industry (SGI) 4.0. In SGI 4.0, the industrial wireless sensor networks (WSNs) and the Internet of Things are envisioned as key promising communication technologies for monitoring various SG applications due to their large‐scale coverage, fault tolerance characteristics, and cost reduction. However, highly dynamic nature of the SG environments brings several unique challenges caused by systems and operating devices. This results in hampering the quality‐of‐service communication requirements for WSNs‐based SG applications. In SGI 4.0, the routing infrastructure not only requires a reliable but also fulfills the communication requirements of diverse SG applications. Thus, a sophisticated, reliable and QoS‐aware multi‐hop communications network architecture enabling a real‐time exchange of data for various WSNs‐based SG applications is essential in SGI 4.0. Hence, this paper proposes a novel bio‐inspired self‐optimized butterfly mating optimization‐based data gathering routing scheme called Self‐optimized Intelligent routing protocol (SIRP) for WSNs‐based SG applications. The extensive simulations reveal that the proposed scheme achieves its defined goals compared to existing routing schemes designed for WSNs‐based applications.

AOA-Based Three-Dimensional Multi-Target Localization in Industrial WSNs for LOS Conditions.

High-precision and fast relative positioning of a large number of mobile sensor nodes (MSNs) is crucial for smart industrial wireless sensor networks (SIWSNs). However, positioning multiple targets simultaneously in three-dimensional (3D) space has been less explored. In this paper, we propose a new approach, called Angle-of-Arrival (AOA) based Three-dimensional Multi-target Localization (ATML). The approach utilizes two anchor nodes (ANs) with antenna arrays to receive the spread spectrum signals broadcast by MSNs. We design a multi-target single-input-multiple-output (MT-SIMO) signal transmission scheme and a simple iterative maximum likelihood estimator (MLE) to estimate the 2D AOAs of multiple MSNs simultaneously. We further adopt the skew line theorem of 3D geometry to mitigate the AOA estimation errors in determining locations. We have conducted extensive simulations and also developed a testbed of the proposed ATML. The numerical and field experiment results have verified that the proposed ATML can locate multiple MSNs simultaneously with high accuracy and efficiency by exploiting the spread spectrum gain and antenna array gain. The ATML scheme does not require extra hardware or synchronization among nodes, and has good capability in mitigating interference and multipath effect in complicated industrial environments.

Node-Identification-Based Secure Time Synchronization in Industrial Wireless Sensor Networks.

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.

Energy Efficient Data Transmission Approaches for Wireless Industrial Automation

Background: The industrial wireless automation system enables the monitoring and control of processes. It may be difficult to recharge the battery of sensors installed in harmful environments. Hence optimization of the power is the major issue to be addressed while implementing the network. The proposed hybrid data transmission approaches optimize data accuracy and energy efficiency of a wireless sensor node deployed in any industry. Methods: In the time-driven method, the sensor nodes periodically sense the environment and transmit the data continuously over time. In the event-driven method, the sensor nodes transmit data only when there is a drastic change in the occurrence of a certain event. Results: Based on the nature of the process, applications are classified as, less critical, critical and most critical. The time-driven based hybrid transmission approach is suggested for the most critical applications because they need to be monitored continuously so as to attain data accuracy. In the case of critical applications, the data is not required to be sent continuously, but instead it can be sampled and transmitted once in two seconds. Though the above suggested methods intended to provide better outcomes in terms of power utilization, in the case of process control applications, most critical and critical applications need to be monitored continuously. Hence such applications could be done as a heterogeneous industrial automation network, which is the combination of wired and wireless connectivity. This can be implemented by replacing all the signal cables with wireless communication system, regular power supply must be provided for the radio module attached with final control elements and also to the transmitters involved in most critical applications. For the least critical applications, the data can be sampled and transmitted once in four seconds. Conclusion: Simulation has been performed for time-driven based and duty-cycling based hybrid transmission approaches. The results can guide process engineers in selecting the transmission approach for optimizing the power of IWAS based on the critical level of the process. In the case of a critical process, the time-driven based hybrid transmission approach may be used, and in the case of a less critical process, the duty-cycling based hybrid transmission approach could be selected. By selecting appropriate transmission approach the life time of IWAS could be improved. Keywords: Controllers, process control, transceivers, transmitters, temperature sensors, wireless sensor networks.

A Framework of Joint Energy Provisioning and Manufacturing Scheduling in Smart Industrial Wireless Rechargeable Sensor Networks.

Energy provisioning is always a crucial problem restricting the further development and application of smart industrial wireless sensor networks in smart factories. In this paper, we present that it is necessary to develop smart industrial wireless rechargeable sensor networks (SIWRSNs) in a smart factory environment. Based on the complexity and time-effectiveness of factory operations, we establish a joint optimization framework named J-EPMS to effectively coordinate the charging strategies of wireless sensors and the scheduling plans of machines running. Then, we propose a novel double chains quantum genetic algorithm with Taboo search (DCQGA-TS) for J-EPMS to obtain a suboptimal solution. The simulation results demonstrate that the DCQGA-TS algorithm can maximally ensure the continuous manufacturing and markedly shorten the total completion time of all production tasks.

A Survey of Anomaly Detection in Industrial Wireless Sensor Networks with Critical Water System Infrastructure as a Case Study.

The increased use of Industrial Wireless Sensor Networks (IWSN) in a variety of different applications, including those that involve critical infrastructure, has meant that adequately protecting these systems has become a necessity. These cyber-physical systems improve the monitoring and control features of these systems but also introduce several security challenges. Intrusion detection is a convenient second line of defence in case of the failure of normal network security protocols. Anomaly detection is a branch of intrusion detection that is resource friendly and provides broader detection generality making it ideal for IWSN applications. These schemes can be used to detect abnormal changes in the environment where IWSNs are deployed. This paper presents a literature survey of the work done in the field in recent years focusing primarily on machine learning techniques. Major research gaps regarding the practical feasibility of these schemes are also identified from surveyed work and critical water infrastructure is discussed as a use case.

A Novel Mobile and Hierarchical Data Transmission Architecture for Smart Factories

In a smart factory environment, a much larger amount of data are transmitted in the workshop networks bringing big challenges to data transfer capability and energy usage efficiency. In the workshop, two main networks, i.e., wired/wireless fieldbus networks and wireless sensor networks, are usually used to collect and transmit data separately; thus, this paper proposes a mobile and hierarchical data transmission architecture to integrate these two networks also taking advantages from the existing mobile intelligence in smart factories, such as automatic guided vehicles (AGVs), to implement a novel data and materials delivery scheme well suited for modern industrial wireless sensor networks (IWSNs). Simulation experiments demonstrated how the proposed approach, running within the IWSN, significantly increases data delivery efficiency along with achieving better energy usage, by 4 times, with respect to the separated networks without any mobile intelligence support.

Fast Convergence Cooperative Dynamic Spectrum Access for Cognitive Radio Networks

Cognitive radio and dynamic spectrum access can reform the way that radiofrequency spectrum is accessed. Problems of spectrum scarcity, coexistence, and unreliable wireless communication that affect industrial wireless networks can be addressed. In this paper, a game theoretic dynamic spectrum access algorithm that improves upon on a hedonic coalition formation algorithm for spectrum sensing and access is presented. The modified algorithm is tailored for faster convergence and scalability and makes use of a novel simultaneous multichannel sensing and access technique. Results to demonstrate the performance improvements of the adapted algorithm are presented and the use of different decision rules are investigated revealing that a conservative decision rule for exploiting spectrum opportunities performs better than an aggressive decision rule in most scenarios. The algorithm that was developed could be a key enabler for future cognitive radio networks.