The growing integration of sensors and embedded devices into distributed Internet of Things (IoT) systems has increased the demand for real-time data collection and processing solutions. However, the high volume and frequency of sensor data create challenges related to storage, transmission, and response latency, especially in resource-constrained environments. In this context, locally executed compression techniques, aligned with the Tiny Machine Learning (TinyML) paradigm, become differentiators for enabling embedded applications. Thus, this work proposes an autoencoder-based approach for efficiently compressing sensor data on edge devices. Three autoencoder variants (feed-forward, sparse, and contractive) are evaluated, combined with symmetric and asymmetric architectures, considering criteria such as compression ratio, information preservation, and embedded execution feasibility. For practical validation, a case study was conducted using vehicular data collected via the OBD-II interface, where the selected models were deployed on the OBDII Edge Freematics One+ device. The results show that the models could reduce data dimensionality with minimal information loss, maintain competitive performance on discriminative tasks, and exhibit inference times compatible with real-time applications. Autoencoders represent a viable neural compression solution for IoT environments, potentially applicable to various embedded sensing scenarios.

The advancement of Industry 4.0 has intensified the demand for intelligent systems that can efficiently access and interpret technical information critical to industrial operations. However, recovering knowledge from extensive and complex technical documentation remains a significant challenge. This study examines the effectiveness of various Retrieval-Augmented Generation (RAG) strategies, combined with different Large Language Models (LLMs), in extracting and generating answers from industrial technical documents. A case study was conducted based on PROFIBUS, a widely adopted digital communication protocol in automation networks, with technical documents organized into categories for engineers and developers. Twenty questions of varying complexity were formulated, and responses were generated using three RAG strategies (Basic, Decomposition, and HyDE) combined with two LLMs (Gemma 3 and GPT-4o-mini). The outputs were compared against reference answers generated by the NotebookLM system and evaluated using automatic metrics, including ROUGE, METEOR, BERTScore, and MATTR. The results indicate that the Decomposition and HyDE strategies achieved superior semantic similarity scores when combined with more capable models. That model’s performance varied depending on the complexity of the document profile. These findings highlight the importance of tailored RAG strategies in enhancing intelligent information retrieval in industrial domains, which supports safer and more efficient operational environments.

The Internet of Things (IoT) generates massive multivariate time series data requiring real-time anomaly detection and correction for reliable monitoring. This challenges resource-constrained embedded devices due to conventional offline training and batch processing. To address this, we propose two algorithms derived from the TEDARLS framework: Multivariate Sequential TEDA (MST) and Multivariate Parallel TEDA (MPT). Derived from the TEDARLS framework, both enable on-device detection and correction of multivariate anomalies within TinyML constraints. A case study with real vehicular sensor data demonstrated low inference times and consistent embedded behavior. Supervised metrics were only assessed on synthetic data. MPT, though more sensitive, introduced greater signal distortions and required significantly longer processing times. Overall, MST demonstrated superior stability and suitability for real-time anomaly correction in resource-constrained IoT environments. This approach addresses an important gap in embedded analytics for IoT by enabling lightweight, accurate, and autonomous anomaly detection and correction at the edge.

Respecting real-time requirements in networked control systems requires that the network traffic respects some well-defined constraints. Any abnormal behavior, e.g. due to malfunctioning of few devices or representing a malicious attack, could disrupt the overall plant behavior. Immediate recognition of anomalies should occur, to determine the causes and mitigate the impairments. Despite hardware sniffer being ready available, deployment cost, maintenance cost and topology constrains of industrial network discourage their adoption for live traffic collection. Additionally, anomaly detection systems are typically complex solutions that demand experienced personnel, which is not generally available among plant maintenance workers. This paper presents the ongoing research activity for a simple but effective expert system that gathers network-related figure of merits natively evaluated by industrial-grade devices, acquired by standard SNMP (Simple Network Management Protocol) queries. Data collected by such a distributed measurement system are further analyzed using simple classification techniques, as the unsupervised clustering, which limit the computational burden. In this work some suitable performance indicators are addressed and the related multi dimensional clustering is discussed. Some preliminary results are provided, exploiting a reference use case designed around a real-world assembly machine.

The Industry 4.0 has led to a significant transformation in manufacturing and industrial processes, characterized by increased connectivity and widespread digitalization. This revolution is driven by the convergence of IT (Information Technology) paradigms with OT (Operational Technology) domains. Virtualization technology plays a crucial role in this integration, thanks to its characteristics of agility, scalability, and efficiency. This work investigates the virtualization of Programmable Logic Controllers (PLCs) and it is focused on the need for evaluating their performance. PLCs are essential components of industrial automation and are being virtualized to increase flexibility, reduce hardware dependencies, and enable seamless integration with IT infrastructures. This work proposes a methodology for evaluating the execution time of a benchmark program and the PLC real-time behavior. Experiments on a real use case demonstrate that the PLCs implemented in containers may be 50 times faster than the real ones in executing data elaboration, while no significant differences were observed in real-time communication. In any case, virtual PLCs are characterized by greater jitter with respect to real PLCs.

The demand for enhanced flexibility in automation systems, dictated by initiatives as the Industry 4.0 in Europe or the Industrial Internet Consortium in the United States, can be satisfied inheriting solutions of the information technology (the so called IT-OT convergence). Other than communication and cloud technologies, virtualization will play a relevant role in the next future. The use of lightweight virtualization, e.g., in the form of containers for implementing the edge computing paradigm, is a promising tool to dynamically provide services depending on the actual production needs. However, requirements of industrial automation applications are different from those of office-like counterparts. For this reason, methodologies for evaluating obtainable performance are needed. In this work, an industrial-grade framework, the Siemens Industrial Edge, is considered. A reference testbed is setup to evaluate latencies when information is exchanged between two user applications. Experiments demonstrate that round trip time in the order of 10 ms is feasible, compatible with the requirements of both process control systems and supervision applications.

LPWAN, an acronym for Low Power Wide Area Network, addresses all the wireless communication solutions aiming at maximize the lifetime of battery powered end devices by means of high-sensitivity radios and sporadic data transactions. Among the different members of the LPWAN family, LoRaWAN is an emerging solution satisfying requirements of many Internet of Things (IoT) related applications. LoRa WAN supports both public and private deployments, operating in unlicensed frequency bands. Handling critical messages, e.g., originated after emergency events in industrial plants, is out of the original LoRaWAN scope. For this reason, the LoRa-REP replication scheme was proposed to increase reliability and to reduce latency of confirmation. In this work, obtainable performance are further improved allowing frame overlaps in time and frequency, exploiting LoRa virtual channels. In particular, Software Defined Radio paradigm is exploited for implementing a proof-of-concept to be used in real-world trials. The preliminary results, supported by simulations as well, are discusses, confirming the feasibility and effectiveness of the proposed approach.

Reliability and dependability are critical demands of the fourth industrial revolution that Real-time Ethernet (RTE) networks have to meet. The use of anomaly detection and prevention techniques can further enhance existing RTE networks. This work presents a general and efficient anomaly detection strategy based on machine learning techniques. The proposal is of general purpose since only normal (i.e not anomalous) traffic data and statistical features are used during the training phase of the classifier. These features are derived from data sets extracted from unsupervised traffic data using a sliding window algorithm. The efficiency of the proposal depends on the proper selection of the sliding window algorithm' parameters. In this work, an optimization strategy appropriately selects the algorithm's step and window size. An Adapted Correlation based on Feature Selection indicates the most relevant features reducing the data dimensionality, improving classifier performance and efficiency. Finally, a One-Class Support Vector Machine algorithm is trained and used for classifying the traffic data sets. The authors applied the proposed anomaly detection strategy in real network data (PROFINET and Ethernet/IP Networks). The results demonstrate the proposal's efficiency and accuracy.

Wireless communications may be the key solution to satisfy mobility, flexibility, and scalability requirements of the Internet of Things. Particularly, the low power wide area networks, operating in unlicensed bands, are promising because they permit both private and public backends. Unfortunately, their target applications are situations where sporadic transmissions are tolerated. They could not fit scenarios in which high reliability and short round trip time are required. In this article, the LoRaWAN solution is considered for managing emergency and alarm communications. Reliability and timeliness limits have been overcome by jointly using a message replication scheme with variable payload length together with low-cost repeaters. Experiments have been carried out in both fixed and low-speed mobility scenarios (with an interfering traffic of 95 message/h, generated by regular LoRaWAN colocated network). Results, in the former case, show that the success probability of confirmed messages is 100%, the 99.6% of the available data are delivered to the backend, and the average delay decreases by 150 ms. When mobility is considered (e.g., for an automatic guided vehicle use case) results confirm significant improvements for both the transaction success ratio and the data extraction rate that significantly increase up to 95% and 87%, respectively. On the contrary, the overall average delay is not always reduced.

Low Power Wide Area Networks (LPWANs) are wireless technologies well accepted in the Internet of Things (IoT) scenarios because they operate in both public and private infrastructure using unlicensed frequency bands. Differently from other wireless standards, the LPWAN target applications are low-rate, sporadic-transmission, low-energy systems. Surely, fast response time and high reliable communication are out of the original LPWAN scope. In this work, a first investigation about the use LoRaWAN (one the most diffused LPWAN protocols) for notification of emergency messages across industrial plants is reported. The opportunity of using recently proposed low-cost repeaters, and the creation of a clever replication pattern of radio messages are the keys of the proposed approach. The results of the preliminary analytical feasibility assessment are presented, confirming the possibility to increase success ratio of notification and respective confirmation in case of emergencies.

Many new narrowband low-power wide-area networks (LPWANs) (e.g., LoRaWAN and Sigfox) have opted to use pure ALOHA-like access for its reduced control overhead and asynchronous transmissions. Although asynchronous access reduces the energy consumption of IoT devices, the network performance suffers from high intranetwork interference in dense deployments. Contrarily, adopting synchronous access can improve throughput and fairness, however, it requires time synchronization. Unfortunately, maintaining synchronization over the narrowband LPWANs wastes channel time and transmission opportunities. In this article, we propose the use of out-of-band time dissemination to relatively synchronize the LoRa devices and thereby facilitate resource-efficient slotted uplink communication. In this respect, we conceptualize and analyze a co-designed synchronization and random access communication mechanism that can effectively exploit technologies providing limited time accuracy, such as FM radio data system (FM-RDS). While considering the LoRa-specific parameters, we derive the throughput of the proposed mechanism, compare it to a generic synchronous random access using in-band synchronization, and design the communication parameters under time uncertainty. We scrutinize the transmission time uncertainty of a device by introducing a clock error model that accounts for the errors in the synchronization source, local clock, propagation delay, and transceiver's transmission time uncertainty. We characterize the time uncertainty of FM-RDS with hardware measurements and perform simulations to evaluate the proposed solution. The results, presented in terms of success probability, throughput, and fairness for a single-cell scenario, suggest that FM-RDS, despite its poor absolute synchronization, can be used effectively to realize time-slotted communication in LoRa with performance similar to that of more accurate time-dissemination technologies.

Recently, designers of the home automation framework are looking to the Internet of Things (IoT) model to make it easier to deploy devices capable of gathering data from various plants. This situation is pushing a further evolution: from the conventional building automation, where the logic is determined by the installer or by the customer, to a cognitive system, capable of learning from the customers' preferences what the best plant configuration would be. The aim of this research work is to identify issues related to the implementation of cognitive solutions during the renovation process of buildings. The paper proposes a cognitive framework to help the operation and management phases of buildings, by means of the digitalization of the supply chain of the construction industry, from the single building aspect to the entire construction cycle. The paper presents the design of smart building elements with integrated capability to generate a massive amount of data for monitoring the energy and maintenance status of renovated buildings. The IoT paradigm has been used to link the physical word of building elements with the cognitive layer. The proposed approach has been applied and validated into a real test case.

The industrial control systems (ICS) are using Real-Time Ethernet (RTE) protocols for many years. Today, Ethernet based control systems are widely used in industries. The Time Sensitive Networking (TSN) initiative will definitely push their further diffusion. With the introduction of Industry 4.0, production machines and their components have been connected to the Internet. Currently adopted RTE protocols do not require authentication, and hence may exchange data also with potentially malicious partners. In this paper, a selective Denial of Service (DoS) attack is presented. The proposed Selective Queue Saturation Attack (SQSA) is aimed to jam the message queue of the RTE communication stack in selected devices. The SQSA minimizes the chances of being detected by keeping its requirements (in term generated traffic) as low as possible. The SQSA has been applied to a real scenario based on PROFINET. The results of the use case demonstrate: the feasibility of the proposed attack; the reduced footprint compared to known DoS attacks (more than one thousand times less); and the selectivity of the attack, which can disrupt the realtime behavior of even a single target node inside the RTE network.

This work deals with the management of sporadic and rare events linked with emergency situations in wireless Internet-of-Things (IoT) scenarios. The goal is to increase the performance of the emergency communication, when low-power wide area networks (LPWANs) are used as IoT backbone. In the proposed approach, a device usually operates as a normal node but, in case of emergency, can use the novel LoRa-REP access method. In this work, the LoRa-REP, based on message replication, is discussed focusing on its capability of reducing average transaction time and increasing success probability. Two operational paradigms have been considered and tested: public LoRaWAN infrastructure with cloud-based backend, and private LoRaWAN networks with local backend (edge/fog computing). Typical examples of public networks are smart cities, whereas local networks are often used in industry or building automation. Additionally, two real use cases (for public and local scenarios) are provided to show the effectiveness of the proposed approach. The experimental results (with a prototype device implementing LoRa-REP and named eNode) show that the success probability of the emergency communication can be increased up to 99.5%, and the average transaction time can be reduced up to 15% with respect to LoRaWAN without retries or up to 50% with respect to LoRaWAN with retries.

The LoRaWAN technology, an example of low power wide area network, is considered a possible IoT-derived solution for realizing private cellular (single-hop) communications in the industrial domain. However, despite LoRaWAN promises long range and dense environments with many obstacles (as the industrial ones), it may suffer from coverage issue. Additionally, the inverse relationship between data rates and range may be unacceptable for many industrial applications. In this article, an innovative LoRaWAN range extender (based on an enhanced LoRaWAN node) is described, and its integration in the infrastructure of industrial Internet of Things (IIoT)-enabled industrial wireless networks is presented. A frame relay strategy is suggested, thus avoiding to tradeoff the highest data rates against an increased sensitivity. The feasibility of the solution is formally verified and the features of the realized proof-of-concept prototype, based on commercially available hardware, are discussed. The experimental results, obtained with a purposely designed test bench, show the effectiveness of the proposed approach. In particular, the range extender is transparent for legacy LoRaWAN networks as confirmed by correct relaying of uplink and downlink for different types of LoRaWAN message.

Internet of things (IoT) is a trend which consists of providing connectivity for many consumer devices. Consequently, a considerable number of applications never seen before is emerging to make daily lifestyle more practical and connected through sharing, storing and processing personal data. When applied to industry, the same technologies can cause a real revolution in the manner how the information is treated. The value of the processed data is increasing fast and point to the fourth industrial revolution, or industry 4.0. This paper evaluates the performance of two ICT (Information and Communication Technology) protocols coming from the consumer world with an enormous potential to be used by industry. Experiments were performed to measure the round trip time using MQTT (Message Queuing Telemetry Transport) and WebSocket protocols with the exchange of data between one server in Italy and another in Brazil. The results can be analyzed for each possible application and different network paths. The average latency samples using each of the protocols were similar, defining the payload size of the requests, but changing according to the way.

In the last decade, the growth of the economic, automotive and technological sectors, has been notable. Alongside this growth, emerges the term ”Industry 4.0” which is used to represent the current Industrial Revolution. This revolution involves different areas: from manufacturing to healthcare. Industry 4.0 can create value during the entire product lifecycle, promoting customer feedback and having the entire product history throughout its life. The automatic communication between vehicle and factory was facilitated, allowing the accomplishment of different analysis regarding vehicles, such as the identification of a behavioral pattern through historical driver usage, fuel consumption, maintenance indicators and so on. This would allow the prevention of critical issues and undesired behaviors as it prevents the automakers from losing contactwiththe vehicle after the purchase. This paper aims to propose a customer feedback platform for vehicle manufacturing in Industry 4.0 context, capable of collecting and analyzing, through an OBD-II scanner the sensors available in vehicles, with the purpose of assisting in the management, prevention, and mitigation of different vehicular problems. An intercontinental experiment conducted in locations within Brazil and Italy show the feasibility of the platform and the potential to use preliminary results in order to improve the vehicle manufacturing.

There are major discussions about the vulnerability of protocols based on real-time Ethernet (RTE) and techniques for detecting anomalies. Thus, this work proposes a methodology for detecting anomalies by optimizing the data extraction and by classifying traffic-related features. In order to cope with this proposal, an artificial neural network (ANN)-based classifier is trained using selected relevant features. These features are extracted using variable sized sliding window and selected according to their correlation with the other features and the expected output of the classifier. The number of relevant features can vary according to performance indicators of the classifier. The proposed methodology was exploited for identifying four different events of PROFINET networks. The performance of the ANN-based classifier was considered successful for all cases. This outcome suggests that the proposed methodology may be successful for anomalies detection in any PROFINET network. However, the application of the proposed methodology to other RTE protocol is foreseen.

Smart Grids deployment is growing around the world. The expansion of the existing Smart Grid network infrastructure in order to connect new electrical substations (or end-users) may be impaired by difficult cable deployment. For this reason, recently, wireless communication links have also been used. This paper deals with the deployment, and the first characterization, of an IEEE 802.11ac connection between IEC 61850 electrical automation devices. Some configurations of IEEE 802.11ac have been tested and compared with usual cable connection. The use of GPS based instrumentation combined with IEEE 1588 clock synchronization allows reducing measurement uncertainty and producing meaningful results. For instance, the IEC 61850 Transfer Time between GOOSE (Generic Object Oriented Substation Event) publisher and subscriber over an IEEE 802.11ac wireless link, loaded with 80Mbit/s of traffic, has an average value of 5.4 ms and a maximum value of 10 ms.

Micro grids are localized groups of electricity generators, energy storage systems, and loads with the possibility of operating both connected and disconnected from the distribution grid. This paper is focused on the automation of micro grids using heterogeneous communication networks; the new approach takes into account the need of reusing existing wired and wireless technologies and assets when planning and deploying new renewable power sources or energy storage systems into traditional (old) grids. The proposed system uses the IEC 61850 in order to guarantee the interoperability with the distribution grid. In addition, the possible synergies with industrial and building automation have been investigated using well-known automation protocols (such as PROFINET and Modbus TCP). The proposed system has been installed and tested in a real micro grid inside the campus of the University of Brescia. Design description, deployment report and result analysis are given, showing that the performance of the real system (i.e. reaction time less than 30 ms at grid level network over heterogeneous links) is in line with the application requirements.

Large industrial automation networks based on Real-Time Ethernet protocols may need efficient multicast management and filtering in order to control traffic load and to guarantee the desired quality of service. Very often industrial network are required to be highly available, implying the use of redundancy protocols, and thus, the use of dynamic (layer 2) multicast reconfiguration may be effective. This paper evaluates the application of standard IEEE Multiple MAC registration Protocol (MMRP) to industrial automation scenarios. Two main application fields are considered: large (and slow) process automation plants; and fast factory automation networks inside electric substations for measuring and protection. Following analytical and simulation approaches complete model of MMRP has been developed. Last, a new set of protocol parameters is proposed to maximize effectiveness of MMRP in industrial scenarios: a great network load reduction and a multicast reconfiguration time of 40 ms after a fault can be obtained in networks with complex topology.

The increased need for power quality monitoring and active control of distribution grid necessitates the introduction of the Smart Grid (SG) approach, requiring an efficient ICT system for the monitoring and control of distribution grid state. The main obstacle to deployment of SG in real system is the lack of an efficient communication infrastructure. The use a heterogeneous network, which employs various technologies, appears to be the most promising solution. Nevertheless, the management of these communication systems has proven to be hard and error prone. In this paper, a Software Defined Networking (SDN) approach has been proposed to manage SG communication system applied to grid monitoring/supervision. The preliminary feasibility analysis is promising, although a more detailed modeling and analysis of the system is needed due to the extreme heterogeneity of the network.

Real-time networks for substations automation systems are based on ICT technologies and they may take great advantages from ultra recent network technological improvements. A careful evaluation of the performance enhancement is required. Due to cost and system complexity, such an analysis can be performed only using a dedicated simulation environment, but the currently available simulation libraries are not focused on lower layers (L1, PHY, and L2 MAC). The main objective of this work is to introduce the architecture of a modular network simulator, with suitable models of L1 and L2 Ethernet layers, for the simulation and co-simulation of substation automation Real-time Ethernet networks. The modular simulator includes interfaces for both co-simulation with FPGA-hardware board and real network, and co-simulation with automation application software (e.g. IEC61850 SCADA system, etc.).

This paper deals with the adoption of wireless communications in industrial automation. Most diffuse wireless systems require the deployment of a fixed infrastructure, with sufficient nodes acting as coordinators; this approach is typically applied also in automation. Conversely, a decentralized wireless solution is here proposed: it is based on a synchronous and connection-oriented protocol studied for vehicular communications. The protocol, called MS-Aloha, guarantees a multi-hop coordination with dynamic resource reservation, spatial slot re-use and hidden terminals prevention. The proposed solution has been modeled and simulated in order to quantitatively demonstrate how much its determinism and multi-hop coordination can be beneficial to the automation, in comparison to CSMA/CA. The simulated scenarios address the evaluation of the latency, delay variation, and delivery rate in critical conditions involving hidden terminals and close to congestion.

The paper describes the application of an improved Time Gateway for simplifying the integration of old IEC 61850 devices in new IEC 61850 Substation Automation System with IEEE 1588 PTP. Old devices typically retrieve time information with the well-known SNTP protocol which uses very different time representations and synchronization strategies with respect to PTP. Hence, the paper uses a transparent, full-software, Time Gateway for interfacing SNTP devices with a PTP synchronization domain, demonstrating its applicability by means of a prototype based on an FPGA. Experimental results show the Time Gateway improves the overall performance with respect to an SNTP-only system. Moreover, the experiments demonstrate that the synchronization accuracy is limited by the SNTP.

The paper presents a case study regarding a real PROFINET IO network for factory automation. The aim of the study is the evaluation of the time related parameter of a real network. A large factory automation plant has been chosen as testbed since PROFINET IO RT Class 1 and 2 (unsynchronized) are mainly used in those applications. The analyzed network has a high number of distributed IO, actuators and sensors; its topology is complex (star and ring); and it is fully operative (in-production). The considered implementation stresses the PROFINET IO communication as no laboratory setup can do, giving meaningful information about real operative conditions on short-term. The results of this case study can be used both to improve simulation models of devices and to verify critical situations in real plants.

Several types of industrial Real-Time Ethernet (RTE) networks could be present in the same plant. This work deals with the clock synchronization problems that arise when different RTE network infrastructures are interconnected. Specifically, this paper is focused on the exploitation of PROFINET IO Conformance Class C infrastructure for the interconnection of other industrial communication devices or measurement instruments that use IEEE1588 for clock synchronization. Actually, such devices (e.g., LXI instruments, EtherNet/IP devices, etc.) cannot be satisfactorily synchronized if directly connected to the PROFINET infrastructure, because of the large time errors (up to 100 μs). The solution proposed in this paper is an intelligent clock synchronization converter that has fewer limitations if compared with other systems, like boundary clocks. The basic idea is the creation of a “black-box” (a sort of remote bridging device) for the interconnection of IEEE1588 nodes through a PROFINET IO host plant, with zero-configuration on both systems. The proposed approach differs from boundary clock since its goal is to keep the PROFINET IO and the IEEE1588 synchronization domains separated, exploiting the possibility to tunnel the IEEE1588 time information through the PROFINET IO infrastructure with sufficient precision. In order to verify the practical feasibility of the proposed solution, LXI Class B instruments have been connected to the infrastructure of a real PROFINET IO network. The results show that the standard deviation of the synchronization accuracy is only 10 ns higher than the one measured in the case of a dedicated (separated) network for the LXI instruments.

The paper deals with IEEE1588 PTP-based devices which are installed in industrial plants together with PROFINET IO Class C. In fact, devices with PTP for clock synchronization (e.g. LXI instruments, Ethernet/IP nodes etc.) exhibit noticeable time errors if directly connected to the PROFINET infrastructure. In the paper, possible architectures to overcome this limitation are evaluated (i.e boundary clock), then an intelligent clock synchronization converter is proposed. The core idea is to create a black-box that does not require configuration neither of the PTP-based nodes nor of the host plant. The proposed converter has been applied to a PROFINET IO network that hosts PTP-based devices. Preliminary results show that, if compared with a direct connection of PTP-based nodes, the converter worsens the synchronization accuracy of less than 10 ns.

This paper deals with the problem of coexistence of wireless sensor networks (WSNs) for industrial applications, proposing new approaches. In fact, if several WSNs operate in the same area, the reliability of the system rapidly decreases, especially if static radio channel assignment WSNs and frequency hopping WSNs are mixed. The proposed architecture is based on a collaborative approach that exploits synchronization capability of some WSNs to improve coexistence. In order to prove the feasibility of this approach, a simulation framework has been created and real prototypes have been evaluated by means of on-the-field measurements. Experimental results, in terms of number of coexisting WSNs and node battery life improvements, show a very good agreement with simulations.

Ethernet technology is widely used in real-time industrial automation. Thanks to real-time Ethernet (RTE) protocols, defined in IEC61784-2 standard, new top-performance automation solutions can be created. Such systems may have communication cycle time down to tens of mus and cycle jitter less than 1 mus, making network testing and debugging very critical. Existing network and protocol analyzers can perform detailed local analysis, but characterization of high-performance RTE systems requires measurement of transmission delays and these instruments cannot be adequately synchronized among them to realize a distributed measurement network. This paper introduces a new low-cost distributed measurement instrument to measure timing characteristics of RTE nodes (end-to-end delays, synchronization, etc.). The proposed instrument has multiple FPGA-based probes that allow for simultaneous/synchronized logging on different place of the target RTE network. A PC-based "monitor station" stores all the data, ready for further elaboration. Architecture details are discussed, a prototype has been realized, and some experimental results are presented. For instance, synchronization accuracy between probes is below 100 ns.

This paper discusses the use of distributed instruments for performance evaluation of real-time Ethernet (RTE) networks. A new instrument, composed of several logging probes connected in different points of a RTE target network, is characterized and compared with commercially available test equipments. The most important problem in performance evaluation is the timestamp assignment to network events; special attention has been paid in measuring synchronization uncertainty among probes. In fact, experimental results show a synchronization accuracy less than 150 ns on timestamp assignments among probes of the same instrument. In the last part of the paper, a sample application on a real network has been described, illustrating the use of the proposed instrument.

The PROFINET architecture can provide real-time, high-performance, isochronous communication regardless the presence of other real-time data exchange and TCP/IP traffic for a considerable portion of network bandwidth. In this work some experimental tests have been executed in order to evaluate timing performance of a PROFINET ASIC (ERTEC 400 chip) and its related development kits. Results shows that communication isochrony has been ensured with a jitter of about 100 ns despite TCP traffic (70% of bandwidth) and presence of PROFINET IO RTjClass 1 nodes. On the contrary, some improvements are still needed as regard features of the software stack and of the interface with the application layerl. The highlighted problems will be probably fixed in the next firmware releases planned by manufacturer.

This paper introduces a new Ethernet based communication system, called GDNET, that allows isochronous I/O management tailored for high-performance plastic machinery. In the typical application (four slaves) GDNET allows 6000 I/O points to be scanned in 200 mus. GDNET is independent from hardware and software choices regarding the PC-based master (processor, network interface card, switches, RTOS...), avoiding the need of a jitter-free clock source, still keeping remote input output synchronization in the order of microseconds. Experimental results show that delay between an event (threshold crossing of an analog input) and the corresponding logic output is 800 mus with a standard deviation below 3 mus. Effectiveness of the proposed system is proved by more than 1400 installations.

This paper deals with real-time Ethernet networks based on PROFINET IO Class 1. Generally, industrial automation has a cyclical behavior; jitter in the application cycle depends on many factors and has direct consequences on production quality. In this work, in order to simplify application jitter estimation of complex systems, measurement techniques are introduced and some initial experiments on real devices are presented. Particularly, methods to experimentally estimate the cycle time of bus, IO-Controller and IO-Devices are proposed. Last, some analytical relations have been obtained: preliminary results show an estimation error less than 5%.