403 research outputs found

    Consensus Algorithms of Distributed Ledger Technology -- A Comprehensive Analysis

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    The most essential component of every Distributed Ledger Technology (DLT) is the Consensus Algorithm (CA), which enables users to reach a consensus in a decentralized and distributed manner. Numerous CA exist, but their viability for particular applications varies, making their trade-offs a crucial factor to consider when implementing DLT in a specific field. This article provided a comprehensive analysis of the various consensus algorithms used in distributed ledger technologies (DLT) and blockchain networks. We cover an extensive array of thirty consensus algorithms. Eleven attributes including hardware requirements, pre-trust level, tolerance level, and more, were used to generate a series of comparison tables evaluating these consensus algorithms. In addition, we discuss DLT classifications, the categories of certain consensus algorithms, and provide examples of authentication-focused and data-storage-focused DLTs. In addition, we analyze the pros and cons of particular consensus algorithms, such as Nominated Proof of Stake (NPoS), Bonded Proof of Stake (BPoS), and Avalanche. In conclusion, we discuss the applicability of these consensus algorithms to various Cyber Physical System (CPS) use cases, including supply chain management, intelligent transportation systems, and smart healthcare.Comment: 50 pages, 20 figure

    Next Generation Business Ecosystems: Engineering Decentralized Markets, Self-Sovereign Identities and Tokenization

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    Digital transformation research increasingly shifts from studying information systems within organizations towards adopting an ecosystem perspective, where multiple actors co-create value. While digital platforms have become a ubiquitous phenomenon in consumer-facing industries, organizations remain cautious about fully embracing the ecosystem concept and sharing data with external partners. Concerns about the market power of platform orchestrators and ongoing discussions on privacy, individual empowerment, and digital sovereignty further complicate the widespread adoption of business ecosystems, particularly in the European Union. In this context, technological innovations in Web3, including blockchain and other distributed ledger technologies, have emerged as potential catalysts for disrupting centralized gatekeepers and enabling a strategic shift towards user-centric, privacy-oriented next-generation business ecosystems. However, existing research efforts focus on decentralizing interactions through distributed network topologies and open protocols lack theoretical convergence, resulting in a fragmented and complex landscape that inadequately addresses the challenges organizations face when transitioning to an ecosystem strategy that harnesses the potential of disintermediation. To address these gaps and successfully engineer next-generation business ecosystems, a comprehensive approach is needed that encompasses the technical design, economic models, and socio-technical dynamics. This dissertation aims to contribute to this endeavor by exploring the implications of Web3 technologies on digital innovation and transformation paths. Drawing on a combination of qualitative and quantitative research, it makes three overarching contributions: First, a conceptual perspective on \u27tokenization\u27 in markets clarifies its ambiguity and provides a unified understanding of the role in ecosystems. This perspective includes frameworks on: (a) technological; (b) economic; and (c) governance aspects of tokenization. Second, a design perspective on \u27decentralized marketplaces\u27 highlights the need for an integrated understanding of micro-structures, business structures, and IT infrastructures in blockchain-enabled marketplaces. This perspective includes: (a) an explorative literature review on design factors; (b) case studies and insights from practitioners to develop requirements and design principles; and (c) a design science project with an interface design prototype of blockchain-enabled marketplaces. Third, an economic perspective on \u27self-sovereign identities\u27 (SSI) as micro-structural elements of decentralized markets. This perspective includes: (a) value creation mechanisms and business aspects of strategic alliances governing SSI ecosystems; (b) business model characteristics adopted by organizations leveraging SSI; and (c) business model archetypes and a framework for SSI ecosystem engineering efforts. The dissertation concludes by discussing limitations as well as outlining potential avenues for future research. These include, amongst others, exploring the challenges of ecosystem bootstrapping in the absence of intermediaries, examining the make-or-join decision in ecosystem emergence, addressing the multidimensional complexity of Web3-enabled ecosystems, investigating incentive mechanisms for inter-organizational collaboration, understanding the role of trust in decentralized environments, and exploring varying degrees of decentralization with potential transition pathways

    Behavior quantification as the missing link between fields: Tools for digital psychiatry and their role in the future of neurobiology

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    The great behavioral heterogeneity observed between individuals with the same psychiatric disorder and even within one individual over time complicates both clinical practice and biomedical research. However, modern technologies are an exciting opportunity to improve behavioral characterization. Existing psychiatry methods that are qualitative or unscalable, such as patient surveys or clinical interviews, can now be collected at a greater capacity and analyzed to produce new quantitative measures. Furthermore, recent capabilities for continuous collection of passive sensor streams, such as phone GPS or smartwatch accelerometer, open avenues of novel questioning that were previously entirely unrealistic. Their temporally dense nature enables a cohesive study of real-time neural and behavioral signals. To develop comprehensive neurobiological models of psychiatric disease, it will be critical to first develop strong methods for behavioral quantification. There is huge potential in what can theoretically be captured by current technologies, but this in itself presents a large computational challenge -- one that will necessitate new data processing tools, new machine learning techniques, and ultimately a shift in how interdisciplinary work is conducted. In my thesis, I detail research projects that take different perspectives on digital psychiatry, subsequently tying ideas together with a concluding discussion on the future of the field. I also provide software infrastructure where relevant, with extensive documentation. Major contributions include scientific arguments and proof of concept results for daily free-form audio journals as an underappreciated psychiatry research datatype, as well as novel stability theorems and pilot empirical success for a proposed multi-area recurrent neural network architecture.Comment: PhD thesis cop

    The EU Cohesion policy and healthy national development: Management and Promotion in Ukraine

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    Монографія присвячена дослідженню сутності принципів реалізації політики згуртованості Європейського Союзу. Авторами проведено аналіз економічних, екологічних та соціальних аспектів інтеграції досвіду ЄС у державну політику України. У монографії узагальнено підходи до відновлення країни та здорового розвитку. Окрему увагу приділено питанням управління системою охорони здоров’я, тенденціям та перспективам досягнення стану стійкості системи медико-соціального забезпечення населення в умовах впливу COVID-19 на національну економіку. Узагальнено досвід використання маркетингових та інноваційних технологій у контексті здорового національного розвитку.Монография посвящена исследованию сущности принципов реализации политики сплоченности Европейского Союза. Авторами проведен анализ экономических, экологических и социальных аспектов интеграции опыта ЕС в государственную политику Украины. В монографии обобщены подходы к восстановлению и здоровому развитию. Отдельное внимание уделено вопросам управления здравоохранением, тенденциям и перспективам достижения состояния устойчивости системы медико-социального обеспечения населения в условиях влияния COVID-19 на национальную экономику. Обобщен опыт использования маркетинговых и инновационных технологий в контексте здорового национального развития.The monograph focused on the specifics of the principles of the EU Cohesion Policy implementation. The authors conducted an analysis of the economic, ecological and social aspects of the integration of the EU experience into the state policy of Ukraine. The monograph summarizes approaches to the restoration of the country and healthy development. Particular attention is paid to the issues of health care system management, the trends and prospects of achieving the state of resilience of the medical and social provision system of the population in the context of the impact of COVID-19 on the national economy. The experience of using marketing and innovative technologies in the context of healthy national development is summarized. The monograph is generally intended for government officials, entrepreneurs, researchers, graduate students, students of economic, medical, and other specialties

    Modern trends in digital transformation of marketing & management

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    The monograph examines the current trends in the development of digital technologies in marketing, management and business administration. The prospects for the development of digital technologies in various sectors of the economy of Ukraine and the trends of the influence of digital technologies on global shifts in the systems of marketing management and business administration are determined. The transformations of business models in the conditions of the digital economy are analyzed, the impact of blockchain technologies on the development of promising areas of the marketing management system and business administration is analyzed. Reasonable impact of digital technologies on the transformation of management systems in social, public, legal and administrative spheres and various sectors of the economy. The contours of the formation of the digital economy in the sectors of economic activity and the social sphere have been developed

    Designing Scalable Mechanisms for Geo-Distributed Platform Services in the Presence of Client Mobility

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    Situation-awareness applications require low-latency response and high network bandwidth, hence benefiting from geo-distributed Edge infrastructures. The developers of these applications typically rely on several platform services, such as Kubernetes, Apache Cassandra and Pulsar, for managing their compute and data components across the geo-distributed Edge infrastructure. Situation-awareness applications impose peculiar requirements on the compute and data placement policies of the platform services. Firstly, the processing logic of these applications is closely tied to the physical environment that it is interacting with. Hence, the access pattern to compute and data exhibits strong spatial affinity. Secondly, the network topology of Edge infrastructure is heterogeneous, wherein communication latency forms a significant portion of the end-to-end compute and data access latency. Therefore, the placement of compute and data components has to be cognizant of the spatial affinity and latency requirements of the applications. However, clients of situation-awareness applications, such as vehicles and drones, are typically mobile – making the compute and data access pattern dynamic and complicating the management of data and compute components. Constant changes in the network connectivity and spatial locality of clients due to client mobility results in making the current placement of compute and data components unsuitable for meeting the latency and spatial affinity requirements of the application. Constant client mobility necessitates that client location and latency offered by the platform services be continuously monitored to detect when application requirements are violated and to adapt the compute and data placement. The control and monitoring modules of off-the-shelf platform services do not have the necessary primitives to incorporate spatial affinity and network topology awareness into their compute and data placement policies. The spatial location of clients is not considered as an input for decision- making in their control modules. Furthermore, they do not perform fine-grained end-to-end monitoring of observed latency to detect and adapt to performance degradations due to client mobility. This dissertation presents three mechanisms that inform the compute and data placement policies of platform services, so that application requirements can be met. M1: Dynamic Spatial Context Management for system entities – clients and data and compute components – to ensure spatial affinity requirements are satisfied. M2: Network Proximity Estimation to provide topology-awareness to the data and compute placement policies of platform services. M3: End-to-End Latency Monitoring to enable collection, aggregation and analysis of per-application metrics in a geo-distributed manner to provide end-to-end insights into application performance. The thesis of our work is that the aforementioned mechanisms are fundamental building blocks for the compute and data management policies of platform services, and that by incorporating them, platform services can meet application requirements at the Edge. Furthermore, the proposed mechanisms can be implemented in a way that offers high scalability to handle high levels of client activity. We demonstrate by construction the efficacy and scalability of the proposed mechanisms for building dynamic compute and data orchestration policies by incorporating them in the control and monitoring modules of three different platform services. Specifically, we incorporate these mechanisms into a topic-based publish-subscribe system (ePulsar), an application orchestration platform (OneEdge), and a key-value store (FogStore). We conduct extensive performance evaluation of these enhanced platform services to showcase how the new mechanisms aid in dynamically adapting the compute/data orchestration decisions to satisfy performance requirements of applicationsPh.D

    Enabling Resilient and Efficient Communication for the XRP Ledger and Interledger

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    The blockchain technology is relatively new and still evolving. Its development was fostered by an enthusiastic community of developers, which sometimes forgot about the lessons from the past related to security, resilience and efficiency of communication which can impact network scalability, service quality and even service availability. These challenges can be addressed at network level but also at operating system level. At network level, the protocols and the architecture used play a major role, and overlays have interesting advantages like custom protocols and the possibility of arbitrary deployments. This thesis shows how overlay networks can be designed and deployed to benefit the security and performance in communication for consensus-validation based blockchains and blockchain inter-operativity, taking as concrete cases the XRP ledger and respectively the Interledger protocol. XRP Ledger is a consensus-validation based blockchain focused on payments which currently uses a flooding mechanism for peer to peer communication, with a negative impact on scalability. One of the proposed overlays is based on Named Data Networking, an Internet architecture using for propagation the data name instead of data location. The second proposed overlay is based on Spines, a solution offering improved latency on lossy paths, intrusion tolerance and resilience to routing attacks. The system component was also interesting to study, and the contribution of this thesis centers around methodologies to evaluate the system performance of a node and increase the security from the system level. The value added by the presented work can be synthesized as follows: i) investigate and propose a Named Data Networking-based overlay solution to improve the efficiency of intra-blockchain communication at network level, taking as a working case the XRP Ledger; ii) investigate and propose an overlay solution based on Spines, which improves the security and resilience of inter-blockchain communication at network level, taking as a working case the Interledger protocol; iii) investigate and propose a host-level solution for non-intrusive instrumentation and monitoring which helps improve the performance and security of inter-blockchain communication at the system level of machines running Distributed Ledger infrastructure applications treated as black-boxes, with Interledger Connectors as a concrete case

    Data replication and update propagation in XML P2P data management systems

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    XML P2P data management systems are P2P systems that use XML as the underlying data format shared between peers in the network. These systems aim to bring the benefits of XML and P2P systems to the distributed data management field. However, P2P systems are known for their lack of central control and high degree of autonomy. Peers may leave the network at any time at will, increasing the risk of data loss. Despite this, most research in XML P2P systems focus on novel and efficient XML indexing and retrieval techniques. Mechanisms for ensuring data availability in XML P2P systems has received comparatively little attention. This project attempts to address this issue. We design an XML P2P data management framework to improve data availability. This framework includes mechanisms for wide-spread data replication, replica location and update propagation. It allows XML documents to be broken down into fragments. By doing so, we aim to reduce the cost of replicating data by distributing smaller XML fragments throughout the network rather than entire documents. To tackle the data replication problem, we propose a suite of selection and placement algorithms that may be interchanged to form a particular replication strategy. To support the placement of replicas anywhere in the network, we use a Fragment Location Catalogue, a global index that maintains the locations of replicas. We also propose a lazy update propagation algorithm to propagate updates to replicas. Experiments show that the data replication algorithms improve data availability in our experimental network environment. We also find that breaking XML documents into smaller pieces and replicating those instead of whole XML documents considerably reduces the replication cost, but at the price of some loss in data availability. For the update propagation tests, we find that the probability that queries return up-to-date results increases, but improvements to the algorithm are necessary to handle environments with high update rates
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