127 research outputs found

    A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

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    In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

    Prospectiva de seguridad de las redes de sensores inalámbricos

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    En las Redes de Sensores Inalámbricos (WSN), los nodos son vulnerables a los ataques de seguridad porque están instalados en un entorno difícil, con energía y memoria limitadas, baja capacidad de procesamiento y transmisión de difusión media; por lo tanto, identificar las amenazas, los retos y las soluciones de seguridad y privacidad es un tema candente hoy en día. En este artículo se analizan los trabajos de investigación que se han realizado sobre los mecanismos de seguridad para la protección de las WSN frente a amenazas y ataques, así como las tendencias que surgen en otros países junto con futuras líneas de investigación. Desde el punto de vista metodológico, este análisis se muestra a través de la visualización y estudio de trabajos indexados en bases de datos como IEEE, ACM, Scopus y Springer, con un rango de 7 años como ventana de observación, desde 2013 hasta 2019. Se obtuvieron un total de 4.728 publicaciones, con un alto índice de colaboración entre China e India. La investigación planteó desarrollos, como avances en los principios de seguridad y mecanismos de defensa, que han llevado al diseño de contramedidas en la detección de intrusiones. Por último, los resultados muestran el interés de la comunidad científica y empresarial por el uso de la inteligencia artificial y el aprendizaje automático (ML) para optimizar las medidas de rendimiento.In Wireless Sensor Networks (WSN), nodes are vulnerable to security attacks because they are installed in a harsh environment with limited power and memory, low processing power, and medium broadcast transmission. Therefore, identifying threats, challenges, and solutions of security and privacy is a talking topic today. This article analyzes the research work that has been carried out on the security mechanisms for the protection of WSN against threats and attacks, as well as the trends that emerge in other countries combined with future research lines. From the methodological point of view, this analysis is shown through the visualization and study of works indexed in databases such as IEEE, ACM, Scopus, and Springer, with a range of 7 years as an observation window, from 2013 to 2019. A total of 4,728 publications were obtained, with a high rate of collaboration between China and India. The research raised developments, such as advances in security principles and defense mechanisms, which have led to the design of countermeasures in intrusion detection. Finally, the results show the interest of the scientific and business community in the use of artificial intelligence and machine learning (ML) to optimize performance measurements

    Fault detection and isolation of malicious nodes in MIMO Multi-hop Control Networks

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    A MIMO Multi-hop Control Network (MCN) consists of a MIMO LTI system where the communication between sensors, actuators and computational units is supported by a (wireless) multi-hop communication network, and data flow is performed using scheduling and routing of sensing and actuation data. We provide necessary and sufficient conditions on the plant dynamics and on the communication protocol configuration such that the Fault Detection and Isolation (FDI) problem of failures and malicious attacks to communication nodes can be solved.Comment: 6 page

    Enhancing graph-routing algorithm for industrial wireless sensor networks

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    Industrial Wireless Sensor Networks (IWSNs) are gaining increasing traction, especially in domains such as the Industrial Internet of Things (IIoT), and the Fourth Industrial Revolution (Industry 4.0). Devised for industrial automation, they have stringent requirements regarding data packet delivery, energy consumption balance, and End-to-End Transmission (E2ET) time. Achieving effective communication is critical to the fulfilment of these requirements and is significantly facilitated by the implementation of graph-routing – the main routing method in the Wireless Highway Addressable Remote Transducer (WirelessHART), which is the global standard of IWSNs. However, graph-routing in IWSN creates a hotspot challenge resulting from unbalanced energy consumption. This issue stems from the typical configuration of WirelessHART paths, which transfers data packets from sensor nodes through mesh topology to a central system called the Network Manager (NM), which is connected to a network gateway. Therefore, the overall aim of this research is to improve the performance of IWSNs by implementing a graph-routing algorithm with unequal clustering and optimisation techniques. In the first part of this thesis, a basic graph-routing algorithm based on unequal clustering topologies is examined with the aim of helping to balance energy consumption, maximise data packet delivery, and reduce the number of hops in the network. To maintain network stability, the creation of static clusters is proposed using the WirelessHART Density-controlled Divide-and-Rule (WDDR) topology. Graph-routing can then be built between Cluster Heads (CHs), which are selected according to the maximum residual energy rate between the sensor nodes in each static cluster. Simulation results indicate that graph-routing with the WDDR topology and probabilistic unequal clustering outperforms mesh topology, even as the network density increased, despite isolated nodes found in the WDDR topology. The second part of this thesis focuses on using the Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. This addresses the three IWSN requirements that form the focus of this research, by proposing three single-objective graph-routing paths: minimum distance (PODis), maximum residual energy (POEng), and minimum end-to-end transmission time (POE2E). The research also adapts the CMA-ES to balance multiple objectives, resulting in the Best Path of Graph-Routing with a CMA-ES (BPGR-ES). Simulation results show that the BPGR-ES effectively balances IWSN requirements, but single-objective paths of graph-routing does not achieve balanced energy consumption with mesh topology, resulting in a significant reduction in the efficiency of the network. Therefore, the third part of this thesis focuses on an Improvement of the WDDR (IWDDR) topology to avoid isolated nodes in the static cluster approaches. The IWDDR topology is used to evaluate the performance of the single-objective graph-routing paths (PODis, POEng, and POE2E). The results show that in IWDDR topology, single-objective graph-routing paths result in more balanced energy consumption

    Exploring Broadband Enabled Smart eEnvironment: Wireless Sensor (Mesh) Network

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    This paper explored the emergent importance of the use sensors as complementary or as alternative to environmental sensing and monitoring, industrial monitoring, and surface explorations. Advances in wireless broadband technology have enabled the use Wireless Sensor (Mesh) Network (WSN), a type mobile ad hoc network (MANET), in all facet of human endeavor. As a next-generation wireless communication, which centered on energy savings, communication reliability, and security, WSN has increased our processing, sensing, and communications capabilities. Hence, this paper is an exploration of recent reliance on sensors as result of broadband enabled smart environment for activities, such as environmental and habitat monitory, military surveillance, target tracking, search and rescue, and logistical tracking and supply-chain management

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    This article presents a novel centrality-driven gateway designation framework for the improved real-time performance of low-power wireless sensor networks (WSNs) at system design time. We target time-synchronized channel hopping (TSCH) WSNs with centralized network management and multiple gateways with the objective of enhancing traffic schedulability by design. To this aim, we propose a novel network centrality metric termed minimal-overlap centrality that characterizes the overall number of path overlaps between all the active flows in the network when a given node is selected as gateway. The metric is used as a gateway designation criterion to elect as a gateway the node leading to the minimal number of overlaps. The method is then extended to multiple gateways with the aid of the unsupervised learning method of spectral clustering. Concretely, after a given number of clusters are identified, we use the new metric at each cluster to designate as cluster gateway the node with the least overall number of overlaps. Extensive simulations with random topologies under centralized earliest-deadline-first (EDF) scheduling and shortest-path routing suggest our approach is dominant over traditional centrality metrics from social network analysis, namely, eigenvector, closeness, betweenness, and degree. Notably, our approach reduces by up to 40% the worst-case end-to-end deadline misses achieved by classical centrality-driven gateway designation methods.This work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDB/04234/2020); by the Operational Competitiveness Programme and Internationalization (COMPETE 2020) under the PT2020 Agreement, through the European Regional Development Fund (ERDF); also by FCT and the ESF (European Social Fund) through the Regional Operational Programme (ROP) Norte 2020, under PhD grant 2020.06685.BD.info:eu-repo/semantics/publishedVersio
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