189 research outputs found

    Design and Real-World Evaluation of Dependable Wireless Cyber-Physical Systems

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    The ongoing effort for an efficient, sustainable, and automated interaction between humans, machines, and our environment will make cyber-physical systems (CPS) an integral part of the industry and our daily lives. At their core, CPS integrate computing elements, communication networks, and physical processes that are monitored and controlled through sensors and actuators. New and innovative applications become possible by extending or replacing static and expensive cable-based communication infrastructures with wireless technology. The flexibility of wireless CPS is a key enabler for many envisioned scenarios, such as intelligent factories, smart farming, personalized healthcare systems, autonomous search and rescue, and smart cities. High dependability, efficiency, and adaptivity requirements complement the demand for wireless and low-cost solutions in such applications. For instance, industrial and medical systems should work reliably and predictably with performance guarantees, even if parts of the system fail. Because emerging CPS will feature mobile and battery-driven devices that can execute various tasks, the systems must also quickly adapt to frequently changing conditions. Moreover, as applications become ever more sophisticated, featuring compact embedded devices that are deployed densely and at scale, efficient designs are indispensable to achieve desired operational lifetimes and satisfy high bandwidth demands. Meeting these partly conflicting requirements, however, is challenging due to imperfections of wireless communication and resource constraints along several dimensions, for example, computing, memory, and power constraints of the devices. More precisely, frequent and correlated message losses paired with very limited bandwidth and varying delays for the message exchange significantly complicate the control design. In addition, since communication ranges are limited, messages must be relayed over multiple hops to cover larger distances, such as an entire factory. Although the resulting mesh networks are more robust against interference, efficient communication is a major challenge as wireless imperfections get amplified, and significant coordination effort is needed, especially if the networks are dynamic. CPS combine various research disciplines, which are often investigated in isolation, ignoring their complex interaction. However, to address this interaction and build trust in the proposed solutions, evaluating CPS using real physical systems and wireless networks paired with formal guarantees of a system’s end-to-end behavior is necessary. Existing works that take this step can only satisfy a few of the abovementioned requirements. Most notably, multi-hop communication has only been used to control slow physical processes while providing no guarantees. One of the reasons is that the current communication protocols are not suited for dynamic multi-hop networks. This thesis closes the gap between existing works and the diverse needs of emerging wireless CPS. The contributions address different research directions and are split into two parts. In the first part, we specifically address the shortcomings of existing communication protocols and make the following contributions to provide a solid networking foundation: • We present Mixer, a communication primitive for the reliable many-to-all message exchange in dynamic wireless multi-hop networks. Mixer runs on resource-constrained low-power embedded devices and combines synchronous transmissions and network coding for a highly scalable and topology-agnostic message exchange. As a result, it supports mobile nodes and can serve any possible traffic patterns, for example, to efficiently realize distributed control, as required by emerging CPS applications. • We present Butler, a lightweight and distributed synchronization mechanism with formally guaranteed correctness properties to improve the dependability of synchronous transmissions-based protocols. These protocols require precise time synchronization provided by a specific node. Upon failure of this node, the entire network cannot communicate. Butler removes this single point of failure by quickly synchronizing all nodes in the network without affecting the protocols’ performance. In the second part, we focus on the challenges of integrating communication and various control concepts using classical time-triggered and modern event-based approaches. Based on the design, implementation, and evaluation of the proposed solutions using real systems and networks, we make the following contributions, which in many ways push the boundaries of previous approaches: • We are the first to demonstrate and evaluate fast feedback control over low-power wireless multi-hop networks. Essential for this achievement is a novel co-design and integration of communication and control. Our wireless embedded platform tames the imperfections impairing control, for example, message loss and varying delays, and considers the resulting key properties in the control design. Furthermore, the careful orchestration of control and communication tasks enables real-time operation and makes our system amenable to an end-to-end analysis. Due to this, we can provably guarantee closed-loop stability for physical processes with linear time-invariant dynamics. • We propose control-guided communication, a novel co-design for distributed self-triggered control over wireless multi-hop networks. Self-triggered control can save energy by transmitting data only when needed. However, there are no solutions that bring those savings to multi-hop networks and that can reallocate freed-up resources, for example, to other agents. Our control system informs the communication system of its transmission demands ahead of time so that communication resources can be allocated accordingly. Thus, we can transfer the energy savings from the control to the communication side and achieve an end-to-end benefit. • We present a novel co-design of distributed control and wireless communication that resolves overload situations in which the communication demand exceeds the available bandwidth. As systems scale up, featuring more agents and higher bandwidth demands, the available bandwidth will be quickly exceeded, resulting in overload. While event-triggered control and self-triggered control approaches reduce the communication demand on average, they cannot prevent that potentially all agents want to communicate simultaneously. We address this limitation by dynamically allocating the available bandwidth to the agents with the highest need. Thus, we can formally prove that our co-design guarantees closed-loop stability for physical systems with stochastic linear time-invariant dynamics.:Abstract Acknowledgements List of Abbreviations List of Figures List of Tables 1 Introduction 1.1 Motivation 1.2 Application Requirements 1.3 Challenges 1.4 State of the Art 1.5 Contributions and Road Map 2 Mixer: Efficient Many-to-All Broadcast in Dynamic Wireless Mesh Networks 2.1 Introduction 2.2 Overview 2.3 Design 2.4 Implementation 2.5 Evaluation 2.6 Discussion 2.7 Related Work 3 Butler: Increasing the Availability of Low-Power Wireless Communication Protocols 3.1 Introduction 3.2 Motivation and Background 3.3 Design 3.4 Analysis 3.5 Implementation 3.6 Evaluation 3.7 Related Work 4 Feedback Control Goes Wireless: Guaranteed Stability over Low-Power Multi-Hop Networks 4.1 Introduction 4.2 Related Work 4.3 Problem Setting and Approach 4.4 Wireless Embedded System Design 4.5 Control Design and Analysis 4.6 Experimental Evaluation 4.A Control Details 5 Control-Guided Communication: Efficient Resource Arbitration and Allocation in Multi-Hop Wireless Control Systems 5.1 Introduction 5.2 Problem Setting 5.3 Co-Design Approach 5.4 Wireless Communication System Design 5.5 Self-Triggered Control Design 5.6 Experimental Evaluation 6 Scaling Beyond Bandwidth Limitations: Wireless Control With Stability Guarantees Under Overload 6.1 Introduction 6.2 Problem and Related Work 6.3 Overview of Co-Design Approach 6.4 Predictive Triggering and Control System 6.5 Adaptive Communication System 6.6 Integration and Stability Analysis 6.7 Testbed Experiments 6.A Proof of Theorem 4 6.B Usage of the Network Bandwidth for Control 7 Conclusion and Outlook 7.1 Contributions 7.2 Future Directions Bibliography List of Publication

    Measuring the impact of COVID-19 on hospital care pathways

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    Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted

    Blockchain-Coordinated Frameworks for Scalable and Secure Supply Chain Networks

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    Supply chains have progressed through time from being limited to a few regional traders to becoming complicated business networks. As a result, supply chain management systems now rely significantly on the digital revolution for the privacy and security of data. Due to key qualities of blockchain, such as transparency, immutability and decentralization, it has recently gained a lot of interest as a way to solve security, privacy and scalability problems in supply chains. However conventional blockchains are not appropriate for supply chain ecosystems because they are computationally costly, have a limited potential to scale and fail to provide trust. Consequently, due to limitations with a lack of trust and coordination, supply chains tend to fail to foster trust among the network’s participants. Assuring data privacy in a supply chain ecosystem is another challenge. If information is being shared with a large number of participants without establishing data privacy, access control risks arise in the network. Protecting data privacy is a concern when sending corporate data, including locations, manufacturing supplies and demand information. The third challenge in supply chain management is scalability, which continues to be a significant barrier to adoption. As the amount of transactions in a supply chain tends to increase along with the number of nodes in a network. So scalability is essential for blockchain adoption in supply chain networks. This thesis seeks to address the challenges of privacy, scalability and trust by providing frameworks for how to effectively combine blockchains with supply chains. This thesis makes four novel contributions. It first develops a blockchain-based framework with Attribute-Based Access Control (ABAC) model to assure data privacy by adopting a distributed framework to enable fine grained, dynamic access control management for supply chain management. To solve the data privacy challenge, AccessChain is developed. This proposed AccessChain model has two types of ledgers in the system: local and global. Local ledgers are used to store business contracts between stakeholders and the ABAC model management, whereas the global ledger is used to record transaction data. AccessChain can enable decentralized, fine-grained and dynamic access control management in SCM when combined with the ABAC model and blockchain technology (BCT). The framework enables a systematic approach that advantages the supply chain, and the experiments yield convincing results. Furthermore, the results of performance monitoring shows that AccessChain’s response time with four local ledgers is acceptable, and therefore it provides significantly greater scalability. Next, a framework for reducing the bullwhip effect (BWE) in SCM is proposed. The framework also focuses on combining data visibility with trust. BWE is first observed in SC and then a blockchain architecture design is used to minimize it. Full sharing of demand data has been shown to help improve the robustness of overall performance in a multiechelon SC environment, especially for BWE mitigation and cumulative cost reduction. It is observed that when it comes to providing access to data, information sharing using a blockchain has some obvious benefits in a supply chain. Furthermore, when data sharing is distributed, parties in the supply chain will have fair access to other parties’ data, even though they are farther downstream. Sharing customer demand is important in a supply chain to enhance decision-making, reduce costs and promote the final end product. This work also explores the ability of BCT as a solution in a distributed ledger approach to create a trust-enhanced environment where trust is established so that stakeholders can share their information effectively. To provide visibility and coordination along with a blockchain consensus process, a new consensus algorithm, namely Reputation-based proof-of cooperation (RPoC), is proposed for blockchain-based SCM, which does not involve validators to solve any mathematical puzzle before storing a new block. The RPoC algorithm is an efficient and scalable consensus algorithm that selects the consensus node dynamically and permits a large number of nodes to participate in the consensus process. The algorithm decreases the workload on individual nodes while increasing consensus performance by allocating the transaction verification process to specific nodes. Through extensive theoretical analyses and experimentation, the suitability of the proposed algorithm is well grounded in terms of scalability and efficiency. The thesis concludes with a blockchain-enabled framework that addresses the issue of preserving privacy and security for an open-bid auction system. This work implements a bid management system in a private BC environment to provide a secure bidding scheme. The novelty of this framework derives from an enhanced approach for integrating BC structures by replacing the original chain structure with a tree structure. Throughout the online world, user privacy is a primary concern, because the electronic environment enables the collection of personal data. Hence a suitable cryptographic protocol for an open-bid auction atop BC is proposed. Here the primary aim is to achieve security and privacy with greater efficiency, which largely depends on the effectiveness of the encryption algorithms used by BC. Essentially this work considers Elliptic Curve Cryptography (ECC) and a dynamic cryptographic accumulator encryption algorithm to enhance security between auctioneer and bidder. The proposed e-bidding scheme and the findings from this study should foster the further growth of BC strategies

    Design and Evaluation of Parallel and Scalable Machine Learning Research in Biomedical Modelling Applications

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    The use of Machine Learning (ML) techniques in the medical field is not a new occurrence and several papers describing research in that direction have been published. This research has helped in analysing medical images, creating responsive cardiovascular models, and predicting outcomes for medical conditions among many other applications. This Ph.D. aims to apply such ML techniques for the analysis of Acute Respiratory Distress Syndrome (ARDS) which is a severe condition that affects around 1 in 10.000 patients worldwide every year with life-threatening consequences. We employ previously developed mechanistic modelling approaches such as the “Nottingham Physiological Simulator,” through which better understanding of ARDS progression can be gleaned, and take advantage of the growing volume of medical datasets available for research (i.e., “big data”) and the advances in ML to develop, train, and optimise the modelling approaches. Additionally, the onset of the COVID-19 pandemic while this Ph.D. research was ongoing provided a similar application field to ARDS, and made further ML research in medical diagnosis applications possible. Finally, we leverage the available Modular Supercomputing Architecture (MSA) developed as part of the Dynamical Exascale Entry Platform~- Extreme Scale Technologies (DEEP-EST) EU Project to scale up and speed up the modelling processes. This Ph.D. Project is one element of the Smart Medical Information Technology for Healthcare (SMITH) project wherein the thesis research can be validated by clinical and medical experts (e.g. Uniklinik RWTH Aachen).Notkun vélnámsaðferða (ML) í læknavísindum er ekki ný af nálinni og hafa nokkrar greinar verið birtar um rannsóknir á því sviði. Þessar rannsóknir hafa hjálpað til við að greina læknisfræðilegar myndir, búa til svörunarlíkön fyrir hjarta- og æðakerfi og spá fyrir um útkomu sjúkdóma meðal margra annarra notkunarmöguleika. Markmið þessarar doktorsrannsóknar er að beita slíkum ML aðferðum við greiningu á bráðu andnauðarheilkenni (ARDS), alvarlegan sjúkdóm sem hrjáir um 1 af hverjum 10.000 sjúklingum á heimsvísu á ári hverju með lífshættulegum afleiðingum. Til að framkvæma þessa greiningu notum við áður þróaðar aðferðir við líkanasmíði, s.s. „Nottingham Physiological Simulator“, sem nota má til að auka skilning á framvindu ARDS-sjúkdómsins. Við nýtum okkur vaxandi umfang læknisfræðilegra gagnasafna sem eru aðgengileg til rannsókna (þ.e. „stórgögn“), framfarir í vélnámi til að þróa, þjálfa og besta líkanaaðferðirnar. Þar að auki hófst COVID-19 faraldurinn þegar doktorsrannsóknin var í vinnslu, sem setti svipað svið fram og ARDS og gerði frekari rannsóknir á ML í læknisfræði mögulegar. Einnig nýtum við tiltæka einingaskipta högun ofurtölva, „Modular Supercomputing Architecture“ (MSA), sem er þróuð sem hluti af „Dynamical Exascale Entry Platform“ - Extreme Scale Technologies (DEEP-EST) verkefnisáætlun ESB til að kvarða og hraða líkanasmíðinni. Þetta doktorsverkefni er einn þáttur í SMITH-verkefninu (e. Smart Medical Information Technology for Healthcare) þar sem sérfræðingar í klíník og læknisfræði geta staðfest rannsóknina (t.d. Uniklinik RWTH Aachen)

    Security and Privacy for Modern Wireless Communication Systems

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    The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

    Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

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    Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida

    Cyber-Human Systems, Space Technologies, and Threats

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    CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp

    Fundamentals

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    Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
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