1,998 research outputs found

    Experimental Evaluation of Techniques to Lower Spectrum Consumption in Wi-Red

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    Seamless redundancy layered atop Wi-Fi has been shown able to tangibly increase communication quality, hence offering industry-grade reliability. However, it also implies much higher network traffic, which is often unbearable as the wireless spectrum is a shared and scarce resource. To deal with this drawback the Wi-Red proposal includes suitable duplication avoidance mechanisms, which reduce spectrum consumption by preventing transmission on air of inessential frame duplicates. In this paper, the ability of such mechanisms to save wireless bandwidth is experimentally evaluated. To this purpose, specific post-analysis techniques have been defined, which permit to carry out such an assessment on a simple testbed that relies on plain redundancy and do not require any changes to the adapters' firmware. As results show, spectrum consumption decreases noticeably without communication quality is impaired. Further saving can be obtained if a slight worsening is tolerated for latencies.Comment: preprint, 13 page

    Seamless Link-level Redundancy to Improve Reliability of Industrial Wi-Fi Networks

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    The adoption of wireless communications and, in particular, Wi-Fi, at the lowest level of the factory automation hierarchy has not increased as fast as expected so far, mainly because of serious issues concerning determinism. Actually, besides the random access scheme, disturbance and interference prevent reliable communication over the air and, as a matter of fact, make wireless networks unable to support distributed real-time control applications properly. Several papers recently appeared in the literature suggest that diversity could be leveraged to overcome this limitation effectively. In this paper a reference architecture is introduced, which describes how seamless link-level redundancy can be applied to Wi-Fi. The framework is general enough to serve as a basis for future protocol enhancements, and also includes two optimizations aimed at improving the quality of wireless communication by avoiding unnecessary replicated transmissions. Some relevant solutions have been analyzed by means of a thorough simulation campaign, in order to highlight their benefits when compared to conventional Wi-Fi. Results show that both packet losses and network latencies improve noticeably.Comment: preprint, 13 pages (Winner of the "2017 Best Paper Award for the IEEE Transactions on Industrial Informatics"

    Analysis of NOMA-Based Retransmission Schemes for Factory Automation Applications

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    New use cases and applications in factory automation scenarios impose demanding requirements for traditional industrial communications. In particular, latency and reliability are considered as some of the most representative Key Performance Indicators (KPI) that limit the technological choices addressing wireless communications. Indeed, there is a considerable research effort ongoing in the area of wireless systems, not only from academia, but also from companies, towards novel solutions that fit Industry 4.0 KPIs. A major limitation for traditional wireless architectures is related to the harsh nature of the industrial propagation channel. Accordingly, this paper addresses these challenges by studying the reliability and latency performance of the joint use of different retransmission schemes in combination with Non-Orthogonal Multiple Access (NOMA) techniques. Two general retransmission schemes have been tested: time-based and spatial diversity-based retransmissions. An adaptive injection level NOMA solution has been combined with the retransmission schemes to improve the reliability of critical information. In all cases, a particular set of simulations has been carried out varying the main parameters, such as modulation, code rate and the injection level. Moreover, the impact of the number of transmitters in relation to the communication reliability has been analyzed. Results show that spatial diversity-based retransmissions overcome considerably the reliability obtained with time-domain retransmissions while maintaining assumable latency ratesThis work was supported in part by the Basque Government under Grant IT1234-19, in part by the PREDOC under Grant PRE_2020_2_0105, and in part by the Spanish Government through project PHANTOM (MCIU/AEI/FEDER, UE) under Grant RTI2018-099162-B-I0

    A study of the applicability of software-defined networking in industrial networks

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    173 p.Las redes industriales interconectan sensores y actuadores para llevar a cabo funciones de monitorización, control y protección en diferentes entornos, tales como sistemas de transporte o sistemas de automatización industrial. Estos sistemas ciberfísicos generalmente están soportados por múltiples redes de datos, ya sean cableadas o inalámbricas, a las cuales demandan nuevas prestaciones, de forma que el control y gestión de tales redes deben estar acoplados a las condiciones del propio sistema industrial. De este modo, aparecen requisitos relacionados con la flexibilidad, mantenibilidad y adaptabilidad, al mismo tiempo que las restricciones de calidad de servicio no se vean afectadas. Sin embargo, las estrategias de control de red tradicionales generalmente no se adaptan eficientemente a entornos cada vez más dinámicos y heterogéneos.Tras definir un conjunto de requerimientos de red y analizar las limitaciones de las soluciones actuales, se deduce que un control provisto independientemente de los propios dispositivos de red añadiría flexibilidad a dichas redes. Por consiguiente, la presente tesis explora la aplicabilidad de las redes definidas por software (Software-Defined Networking, SDN) en sistemas de automatización industrial. Para llevar a cabo este enfoque, se ha tomado como caso de estudio las redes de automatización basadas en el estándar IEC 61850, el cual es ampliamente usado en el diseño de las redes de comunicaciones en sistemas de distribución de energía, tales como las subestaciones eléctricas. El estándar IEC 61850 define diferentes servicios y protocolos con altos requisitos en terminos de latencia y disponibilidad de la red, los cuales han de ser satisfechos mediante técnicas de ingeniería de tráfico. Como resultado, aprovechando la flexibilidad y programabilidad ofrecidas por las redes definidas por software, en esta tesis se propone una arquitectura de control basada en el protocolo OpenFlow que, incluyendo tecnologías de gestión y monitorización de red, permite establecer políticas de tráfico acorde a su prioridad y al estado de la red.Además, las subestaciones eléctricas son un ejemplo representativo de infraestructura crítica, que son aquellas en las que un fallo puede resultar en graves pérdidas económicas, daños físicos y materiales. De esta forma, tales sistemas deben ser extremadamente seguros y robustos, por lo que es conveniente la implementación de topologías redundantes que ofrezcan un tiempo de reacción ante fallos mínimo. Con tal objetivo, el estándar IEC 62439-3 define los protocolos Parallel Redundancy Protocol (PRP) y High-availability Seamless Redundancy (HSR), los cuales garantizan un tiempo de recuperación nulo en caso de fallo mediante la redundancia activa de datos en redes Ethernet. Sin embargo, la gestión de redes basadas en PRP y HSR es estática e inflexible, lo que, añadido a la reducción de ancho de banda debida la duplicación de datos, hace difícil un control eficiente de los recursos disponibles. En dicho sentido, esta tesis propone control de la redundancia basado en el paradigma SDN para un aprovechamiento eficiente de topologías malladas, al mismo tiempo que se garantiza la disponibilidad de las aplicaciones de control y monitorización. En particular, se discute cómo el protocolo OpenFlow permite a un controlador externo configurar múltiples caminos redundantes entre dispositivos con varias interfaces de red, así como en entornos inalámbricos. De esta forma, los servicios críticos pueden protegerse en situaciones de interferencia y movilidad.La evaluación de la idoneidad de las soluciones propuestas ha sido llevada a cabo, principalmente, mediante la emulación de diferentes topologías y tipos de tráfico. Igualmente, se ha estudiado analítica y experimentalmente cómo afecta a la latencia el poder reducir el número de saltos en las comunicaciones con respecto al uso de un árbol de expansión, así como balancear la carga en una red de nivel 2. Además, se ha realizado un análisis de la mejora de la eficiencia en el uso de los recursos de red y la robustez alcanzada con la combinación de los protocolos PRP y HSR con un control llevado a cabo mediante OpenFlow. Estos resultados muestran que el modelo SDN podría mejorar significativamente las prestaciones de una red industrial de misión crítica

    A Comprehensive Review on Time Sensitive Networks with a Special Focus on Its Applicability to Industrial Smart and Distributed Measurement Systems

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    The groundbreaking transformations triggered by the Industry 4.0 paradigm have dramati-cally reshaped the requirements for control and communication systems within the factory systems of the future. The aforementioned technological revolution strongly affects industrial smart and distributed measurement systems as well, pointing to ever more integrated and intelligent equipment devoted to derive accurate measurements. Moreover, as factory automation uses ever wider and complex smart distributed measurement systems, the well-known Internet of Things (IoT) paradigm finds its viability also in the industrial context, namely Industrial IoT (IIoT). In this context, communication networks and protocols play a key role, directly impacting on the measurement accuracy, causality, reliability and safety. The requirements coming both from Industry 4.0 and the IIoT, such as the coexistence of time-sensitive and best effort traffic, the need for enhanced horizontal and vertical integration, and interoperability between Information Technology (IT) and Operational Technology (OT), fostered the development of enhanced communication subsystems. Indeed, established tech-nologies, such as Ethernet and Wi-Fi, widespread in the consumer and office fields, are intrinsically non-deterministic and unable to support critical traffic. In the last years, the IEEE 802.1 Working Group defined an extensive set of standards, comprehensively known as Time Sensitive Networking (TSN), aiming at reshaping the Ethernet standard to support for time-, mission-and safety-critical traffic. In this paper, a comprehensive overview of the TSN Working Group standardization activity is provided, while contextualizing TSN within the complex existing industrial technological panorama, particularly focusing on industrial distributed measurement systems. In particular, this paper has to be considered a technical review of the most important features of TSN, while underlining its applicability to the measurement field. Furthermore, the adoption of TSN within the Wi-Fi technology is addressed in the last part of the survey, since wireless communication represents an appealing opportunity in the industrial measurement context. In this respect, a test case is presented, to point out the need for wirelessly connected sensors networks. In particular, by reviewing some literature contributions it has been possible to show how wireless technologies offer the flexibility necessary to support advanced mobile IIoT applications

    GLEm-Net: Unified Framework for Data Reduction with Categorical and Numerical Features

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    In the era of Big Data, effective data reduction through feature selection is of paramount importance for machine learning. This paper presents GLEm-Net (Grouped Lasso with Embeddings Network), a novel neural framework that seamlessly processes both categorical and numerical features to reduce the dimensionality of data while retaining as much information as possible. By integrating embedding layers, GLEm-Net effectively manages categorical features with high cardinality and compresses their information in a less dimensional space. By using a grouped Lasso penalty function in its architecture, GLEm-Net simultaneously processes categorical and numerical data, efficiently reducing high-dimensional data while preserving the essential information. We test GLEm-Net with a real-world application in an industrial environment where 6 million records exist and each is described by a mixture of 19 numerical and 7 categorical features with a strong class imbalance. A comparative analysis using state-of-the-art methods shows that despite the difficulty of building a high-performance model, GLEm-Net outperforms the other methods in both feature selection and classification, with a better balance in the selection of both numerical and categorical features
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