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Doctrina: Blockchain 5.0 for Artificial Intelligence

APPLIED SCIENCES-BASEL 2025年第10期15卷 5602-5602页

作者： Tulkinbekov, Khikmatullo Kim, Deok-Hwan Inha Univ Dept Elect & Comp Engn Incheon 22210 South Korea

The convergence of blockchain technology with artificial intelligence presents a promising paradigm shift in data management and trust within AI ecosystems. Starting from the initial cryptocurrency-oriented versions, the blockchain potential is improved up to the highly scalable and programmable versions available currently. Even though the integration of real-world applications offers a promising future for distributed computing, there are limitations on executing AI models on blockchain due to high external library dependencies, storage, and cost constraints. Addressing this issue, this study explores the transformative potential of integrating blockchain with AI within the paradigm of blockchain 5.0. We propose the next-generation novel blockchain architecture named Doctrina that allows executing AI models directly on blockchain. Compared to the existing approaches, Doctrina allows sharing and using AI services in a fully distributed and privacy-preserved manner.

关键词： blockchain artificial intelligence blockchain 5.0 smart contracts distributed computing AI model execution blockchain AI integration

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Globus automation services: Research process automation across the space-time continuum

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2023年 142卷 393-409页

作者： Chard, Ryan Pruyne, Jim McKee, Kurt Bryan, Josh Raumann, Brigitte Ananthakrishnan, Rachana Chard, Kyle Foster, Ian T. Argonne Natl Lab 9700 S Cass Ave Lemont IL 60439 USA Univ Chicago 5730 S Ellis Ave Chicago IL 60615 USA

Research process automation-the reliable, efficient, and reproducible execution of linked sets of actions on scientific instruments, computers, data stores, and other resources-has emerged as an essential element of modern science. We report here on new services within the Globus research data management platform that enable the specification of diverse research processes as reusable sets of actions, flows, and the execution of such flows in heterogeneous research environments. To support flows with broad spatial extent (e.g., from scientific instrument to remote data center) and temporal extent (from seconds to weeks), these Globus automation services feature: (1) cloud hosting for reliable execution of even long-lived flows despite sporadic failures;(2) a simple specification and extensible asynchronous action provider API, for defining and executing a wide variety of actions and flows involving heterogeneous resources;(3) an event-driven execution model for automating execution of flows in response to arbitrary events;and (4) a rich security model enabling authorization delegation mechanisms for secure execution of long-running actions across distributed resources. These services permit researchers to outsource and automate the management of a broad range of research tasks to a reliable, scalable, and secure cloud platform. We present use cases for Globus automation services, describe their design and implementation, present microbenchmark studies, and review experiences applying the services in a range of applications.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Research process automation Globus High-performance computing distributed computing Scientific computing Cloud computing

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Federated Learning for Computationally Constrained Heterogeneous Devices: A Survey

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ACM computing SURVEYS 2023年第14S期55卷 1-27页

作者： Pfeiffer, Kilian Rapp, Martin Khalili, Ramin Henkel, Joerg Karlsruhe Inst Technol Karlsruhe Germany Huawei Technol Munich Res Ctr Munich Germany

With an increasing number of smart devices like internet of things devices deployed in the field, offloading training of neural networks (NNs) to a central server becomes more and more infeasible. Recent efforts to improve users' privacy have led to on-device learning emerging as an alternative. However, a model trained only on a single device, using only local data, is unlikely to reach a high accuracy. Federated learning (FL) has been introduced as a solution, offering a privacy-preserving tradeoff between communication overhead and model accuracy by sharing knowledge between devices but disclosing the devices' private data. The applicability and the benefit of applying baseline FL are, however, limited in many relevant use cases due to the heterogeneity present in such environments. In this survey, we outline the heterogeneity challenges FL has to overcome to be widely applicable in real-world applications. We especially focus on the aspect of computation heterogeneity among the participating devices and provide a comprehensive overview of recent works on heterogeneity-aware FL. We discuss two groups: works that adapt the NN architecture and works that approach heterogeneity on a system level, covering Federated Averaging, distillation, and split learning-based approaches, as well as synchronous and asynchronous aggregation schemes.

关键词： Machine learning federated learning resource-constraints heterogeneous distributed computing

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High Frequency Model of Power Transformer Bushing for Very Fast Transient Studies

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IEEE ACCESS 2023年 11卷 93908-93919页

作者： Messadi, Anes Zouaghi, Ayyoub Ferdjallah-Kherkhachi, Esseddik Vollaire, Christian Richer, Olivier de Oliveira, Luiz Fernando Breard, Arnaud Univ Claude Bernard Lyon 1 Univ Lyon Ecole Cent Lyon INSA LyonAmpereCNRSUMR5005 F-69130 Ecully France Trench France Res & Dev Dept F-68300 St Louis France WEG Equipamentos Eletr SA Res & Dev Dept BR-89256900 Blumenau Brazil

Fast and very fast transient overvoltages generally appear during switching operations within electrical substations. The oscillatory nature of such phenomena with frequencies that can reach several tens of megahertz tends to degrade the lifetime of high voltage equipment such as bushings and transformers, inducing partial discharges activity or breakdown of the insulation system. According to several case studies, bushings are one of the most sensitive parts to such overvoltages, indeed, a failure in a bushing will in most cases lead to a failure of the transformer, often catastrophically. Generating such overvoltages with a very high frequency character and considerable amplitude can be very difficult, moreover, studying the effect of such overvoltages on the insulated bushings is not easy, even experimentally. Therefore, a simulation of the fast transients in the system can be very useful to understand the consequences of such phenomena. In this context, this document aims to propose a model of high voltage capacitive graded oil impregnated paper (OIP) bushing based on a distributed electrical circuit. The equivalent circuit is constructed based on the geometric design and electrical properties of the materials. The model was developed and implemented using Matlab/Simulink (R) Software, and was validated with experimental measurements based on impedance sweep frequency analysis. The modeling results are in a good agreement with the experimental ones.

关键词： Insulators Integrated circuit modeling Impedance Surges Power transformer insulation Frequency measurement Transient analysis distributed computing Voltage control Bushing distributed circuit model high voltage high frequency impedance analysis numerical modeling overvoltage power transformer very fast transient

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The D4Science Experience on Virtual Research Environment Development

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computing IN SCIENCE & ENGINEERING 2023年第2期25卷 12-19页

作者： Candela, Leonardo Castelli, Donatella Pagano, Pasquale Natl Res Council Italy Ist Sci & Tecnol Informaz A Faedo I-56124 Pisa Italy

Today, complex research challenges, often based on the analysis of a large amount of data, require multidisciplinary collaboration as well as appropriate communication and sharing of data, processes, and outcomes. Technologies and large-scale infrastructures provide stakeholders with computing capacity and data services to perform unprecedented levels of data-driven scientific activities. This opens the way to science gateways and virtual research environments (VREs) supporting researchers in scientific and educational activities. This article describes our extensive experience with the VREs operated by the D4Science infrastructure. It presents how this infrastructure supports their development and their basic functionalities as well as how they are easily customized to serve the needs of specific user communities. It also describes how they are used in real contexts. The article concludes by reporting how VREs are now progressively used as valuable instruments to support open science and how this role might become more relevant in the future.

关键词： Task analysis Training Portals Logic gates distributed computing Data analysis Collaboration

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Group Secret Key Generation Using Physical Layer Security for UAV Swarm Communications

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2023年第6期59卷 8550-8564页

作者： Jangsher, Sobia Al-Dweik, Arafat Iraqi, Youssef Pandey, Anshul Giacalone, Jean-Pierre Khalifa Univ Dept Elect Engn & Comp Sci Abu Dhabi 127788 U Arab Emirates Dublin City Univ Dublin Ireland Khalifa Univ Ctr Cyber Phys Syst Abu Dhabi 127788 U Arab Emirates Western Univ Dept Elect & Comp Engn London ON N6A 3K7 Canada Mohammed VI Polytech Univ Coll Comp Ben Guerir 43150 Morocco Technol & Innovat Inst Secure Syst Res Ctr Abu Dhabi 9639 U Arab Emirates

In unmanned aerial vehicle (UAV) swarm networks, a group secret key (GSK) is required to enable secured UAV-UAV communications, multicast, and broadcast transmission. Moreover, it can be used for device authentication. Therefore, this article proposes an efficient GSK protocol denoted as the sequential secret group key (SSGK) algorithm for distributed UAV swarm-secured communications. The proposed protocol utilizes network coding to generate cooperation information that is transmitted on the channel and is uncorrelated with the generated secret key. The proposed protocol depends on the pairwise key generation process between pairs of UAVs. However, not all possible pairwise agreements are performed to minimize the time and signaling overhead, i.e., the pairwise key agreement is performed only between selected UAVs as a compromise between the required overhead transmission resources and the achieved redundancy level. The obtained results show that a redundancy level of 4 is sufficient to provide a reliable GSK generation process. The results also show that the performance of the key generation process highly depends on the channel bit error rate (BER), the number of UAVs, and the key length.

关键词： Autonomous aerial vehicles Authentication Redundancy Mesh networks Complexity theory Security Protocols distributed computing group key (GK) mesh networks network coding physical layer security (PLS) physically unclonable function (PUF) unmanned aerial vehicle (UAV)

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CWL-PLAS: Task Workflows Assisted by Data Science Cloud Platforms

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IEEE ACCESS 2023年 11卷 44092-44106页

作者： Detti, Andrea Funari, Ludovico Petrucci, Luca Dorazio, Michele Mencattini, Arianna Martinelli, Eugenio Univ Roma Tor Vergata Dept Elect Engn Rome 00133 Italy Natl Interuniv Consortium Telecommun CNIT I-43124 Parma Italy Interdisciplinary Ctr Adv Study Organ Onchip I-00133 Rome Italy Lab Onchip Applicat LOC I-00133 Rome Italy

The Common Workflow Language (CWL) is a platform-independent description language for the representation of data science workflows consisting of a set of tasks that interact with each other to perform scientific analysis. The tasks can be packaged as Linux containers. On the one hand, using containers ensures the reproducibility and portability of workflows. Still, on the other hand, it limits each task to exploiting, at most, the resources of the host where its container runs. In this paper, we propose CWL-PLAS, an extension of CWL that allows a task to instantiate and temporarily use a supporting cloud platform for parallel computing, which is specialized for the task's activity. In this way, tasks can leverage the resources of multiple hosts in parallel, reducing the duration of the workflow. We implemented an open-source workflow manager that supports CWL-PLAS workflows and exploits a Kubernetes back-end. We used this workflow manager to evaluate the performance of CWL-PLAS in a couple of machine learning workflows.

关键词： Computer languages Software management and development Parallel processing Processor scheduling Standards Portfolios distributed computing Common workflow language workflow management software distributed computing cloud

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A General Purpose Data and Query Privacy Preserving Protocol for Wireless Sensor Networks

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023年 18卷 4883-4898页

作者： Hrovatin, Niki Tosic, Aleksandar Mrissa, Michael Vicic, Jernej InnoRenew CoE Izola 6310 Slovenia Univ Primorska Fac Math Nat Sci & Informat Technol Koper 6000 Slovenia Fran Ramovs Inst Res Ctr Slovenian Acad Sci & Arts Ljubljana 1000 Slovenia

The large number of devices characterizing Wireless Sensor Networks (WSNs) provide the benefits of observing, tracking, and recording everything;nonetheless, the cumulative computing power of those devices is typically not utilized, and the few implementations taking advantage of it neglect privacy or are application-specific. This manuscript describes a privacy-preserving protocol that enables WSN nodes to jointly compute an arbitrary function without disclosing their own private inputs. The computation takes place at data source nodes, while computation instructions and intermediate results move across the network secured by cryptography. The protocol relies on the Onion Routing technique to provide uniformly distributed network traffic and confine the knowledge a foreign actor can gain from monitoring messages traveling the network. We show that the communication protocol is privacy-preserving against the external and internal attacker models, and we validate our protocol implementation using the NS3 network simulator.

关键词： Wireless sensor network privacy onion routing distributed computing data aggregation

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Divide-and-Conquer Fusion

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JOURNAL OF MACHINE LEARNING RESEARCH 2023年第1期24卷 1-82页

作者： Chan, Ryan S. Y. Pollock, Murray Johansen, Adam M. Roberts, Gareth O. Alan Turing Inst London NW1 2DB England Newcastle Univ Sch Math Stat & Phys Newcastle NE1 7RU England Univ Warwick Dept Stat Coventry CV4 7AL England

Combining several (sample approximations of) distributions, which we term sub-posteriors, into a single distribution proportional to their product, is a common challenge. Occurring, for instance, in distributed 'big data' problems, or when working under multi-party privacy constraints. Many existing approaches resort to approximating the individual subposteriors for practical necessity, then find either an analytical approximation or sample approximation of the resulting (product-pooled) posterior. The quality of the posterior approximation for these approaches is poor when the sub-posteriors fall out-with a narrow range of distributional form, such as being approximately Gaussian. Recently, a Fusion approach has been proposed which finds an exact Monte Carlo approximation of the posterior, circumventing the drawbacks of approximate approaches. Unfortunately, existing Fusion approaches have a number of computational limitations, particularly when unifying a large number of sub-posteriors. In this paper, we generalise the theory underpinning existing Fusion approaches, and embed the resulting methodology within a recursive divide-andapproach, which is robust to increasing numbers of sub-posteriors.

关键词： distributed computing importance sampling Markov chain Monte Carlo sequential Monte Carlo stochastic differential equations

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Indexing legacy data-sets for global access and processing in multi-cloud environments

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2023年第1期148卷 150-159页

作者： Orzechowski, Michal Wrzeszcz, Michal Kryza, Bartosz Dutka, Lukasz Slota, Renata G. Kitowski, Jacek Acad Comp Ctr CYFRONET AGH Nawojki 11 PL-30950 Krakow Poland AGH Univ Krakow Adama Mickiewicza 30 PL-30059 Krakow Poland

Global data access and processing for multi-cloud applications proves challenging where there is a need for efficient access to large pre-existing, legacy data-sets. To address this problem, we created an indexing subsystem, allowing us to index and gather the metadata of legacy data-sets. The gathered information is later incorporated into a multi-cloud data management system to achieve global integration of legacy storage systems containing large data-sets. The solution is based on metadata management, organization and periodic monitoring of legacy data-sets, which makes possible scheme-less co-existence of a legacy storage system and a multi-cloud data management system for managing the same data collections. The approach has been initially evaluated in a multi-cloud deployment scenario. A large data collection consisting of legacy cultural data-sets was exposed to public and commercial infrastructure for data access and processing.& COPY;2023 Published by Elsevier B.V.

关键词： Data management system Metadata management Legacy data Multi-cloud distributed computing

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