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Unleashing the Potential of Decentralized Federated Learning in Healthcare: A Comprehensive Survey on Insights and Challenges

Unleashing the Potential of Decentralized Federated Learning...

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IEEE international conference on Data Science in Cyberspace (DSC)

作者： Haibo Cheng Wenjian Liu Youyang Qu Kexue Fu Qinyuan Wang Faculty of Data Science City University of Macau Macau China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

Federated learning (FL) is a distributed learning method that reduces data transmission and privacy risks. However, the existence of a central server may become a target of attackers, resulting in an increased risk of user privacy leakage. the emergence of Decentralized Federated Learning (DFL) is posited to enhance data privacy and system reliability by reducing reliance on central servers and enhancing local data control, especially in the medical field, where personal health data is protected. this research investigates the application of (DFL) in the medical domain, focusing on its limitations. this study employs a systematic literature review, adhering to PRISMA guidelines, to comprehensively understand DFL’s current landscape and challenges in healthcare. the key findings highlight four principal obstacles faced by DFL: security and privacy, communication efficiency, data and model heterogeneity, and incentive mechanisms. It also explores the potential for DFL to facilitate personalized healthcare treatments by large datasets distributed across various medical institutions. this research fills a significant void by systematically reviewing DFL technologies in healthcare. It provides insights into applications, challenges, and future directions for participants seeking secure and efficient healthcare data handling.

关键词： Surveys Data privacy Systematics Federated learning Medical services Data models Servers Security Reliability Systematic literature review

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DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices 9

DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Dev...

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9th IEEE international conference on Cloud Engineering (IC2E)

作者： Baller, Stephan Patrick Jindal, Anshul Chadha, Mohak Gerndt, Michael Tech Univ Munich Chair Comp Architecture & Parallel Syst Garching Germany

ISBN: (纸本)9781665449700

EdgeAI (Edge computing based Artificial Intelligence) has been most actively researched for the last few years to handle variety of massively distributed AI applications to meet up the strict latency requirements. Meanwhile, many companies have released edge devices with smaller form factors (low power consumption and limited resources) like the popular Raspberry Pi and Nvidia's Jetson Nano for acting as compute nodes at the edge computing environments. Although the edge devices are limited in terms of computing power and hardware resources, they are powered by accelerators to enhance their performance behavior. therefore, it is interesting to see how AI-based Deep Neural Networks perform on such devices with limited resources. In this work, we present and compare the performance in terms of inference time and power consumption of the four SoCs: Asus Tinker Edge R, Raspberry Pi 4, Google Coral Dev Board, Nvidia Jetson Nano, and one microcontroller: Arduino Nano 33 BLE, on different deep learning models and frameworks. We also provide a method for measuring power consumption, inference time and accuracy for the devices, which can be easily extended to other devices. Our results showcase that, for Tensorflow based quantized model, the Google Coral Dev Board delivers the best performance, both for inference time and power consumption. For a low fraction of inference computation time, i.e. less than 29.3% of the time for MobileNetV2, the Jetson Nano performs faster than the other devices.

关键词： edge computing deep learning performance benchmark edge devices power consumption inference time power prediction

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DESIGN and DEVELOPMENT of APPLICATION SOFTWARE for the MPD distributed computing INFRASTRUCTURE 9

DESIGN and DEVELOPMENT of APPLICATION SOFTWARE for the MPD D...

引用

9th international conference "distributed computing and Grid Technologies in Science and Education", GRID 2021

作者： Moshkin, Andrey Pelevanyuk, Igor Rogachevskiy, Oleg Joint Institute for Nuclear Research 6 Joliot-Curie St. Moscow Region Dubna 141980 Russia

the Multi-Purpose Detector collaboration began using distributed computing for centralized Monte-Carlo generation in mid-2019. the DIRAC Interware is used as a platform for the integration of heterogeneous distributed computing resources. Since then, workflows of job submission, data transfer, and storage have been designed, tested, and successfully applied. Moreover, the growth of interest in access to the computing system from users is observed. One way to provide such access for the users is to allow them to directly submit jobs to DIRAC. However, direct access to the resources imposes a high responsibility on users and must be restricted. For this reason, another approach was chosen, i.e. to design and develop a dedicated application that collects requirements from users and starts the required number of jobs. Such an approach entails additional effort: elaboration of requirements, application design and development. Nevertheless, it allows for greater control over the workload submitted by other users, reducing possible failures and the inefficient usage of resources. © 2021 CEUR-WS. All rights reserved.

关键词： Data transfer

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Decentralized Identifiers and Self-Sovereign Identity - A New Identity Management for 6G Integration?

Decentralized Identifiers and Self-Sovereign Identity - A Ne...

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12th IEEE international conference on Joint Cloud computing (IEEE JCC) / 9th IEEE international conference on Mobile Cloud computing, Services, and Engineering (IEEE MobileCloud)

作者： Kuepper, Axel TU Berlin T Labs Serv Ctr Networking Berlin Germany

ISBN: (纸本)9781665434799

Decentralized Identifiers (DIDs) and Self-Sovereign Identity (SSI) are emerging decentralized identity solutions. DIDs allow legal entities like organizations to create and fully control their identifiers while building the necessary infrastructure for SSI, enabling entities like persons, organizations, or machines to fully control and own their digital identities without the involvement of an intermediate central authority. DIDs are identifiers that are used to reference entities unambiguously and, together with DID Documents stored in a verifiable data registry, establish a new, decentralized public-key infrastructure. An SSI-based digital identity may be composed of many different claims certified by an issuer. Examples are the identity holder’s name, age, gender, university degree, driving license, or other attributes. What makes SSI unique compared to other identity management solutions is that the users keep their digital identities in storage of their choice and thus determine their distribution and *** this privacy-by-design approach, the emergence of DIDs and SSI can shape the architecture of the future Internet and its applications, which will impact the future of mobile networks. While 5G networks are currently being rolled out, a discussion about the new capabilities of 6G networks, which are still in the distant future, has long since begun. In addition to even faster access, shorter delays, and new applications, features such as human-centricity, data protection, and privacy are being addressed in particular in the discussions. these latter points make DIDs, SSI, and related concepts and architectures promising candidates for 6G *** talk gives a brief introduction to DIDs and SSI and then discusses the benefits and drawbacks the integration of these technologies into 6G may have. Furthermore, the talk identifies different use cases and identifies the system components and functions of cellular networks affected by a 6G integration.

关键词： 6G mobile communication Shape Law conferences Public key Data protection Organizations

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JINR distributed INFORMATION and computing ENVIRONMENT: PARTICIPANTS, FEATURES and CHALLENGES 9

JINR DISTRIBUTED INFORMATION and COMPUTING ENVIRONMENT: PART...

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9th international conference "distributed computing and Grid Technologies in Science and Education", GRID 2021

作者： Balashov, Nikita Kuprikov, Igor Kutovskiy, Nikolay Makhalkin, Alexandr Mazhitova, Yelena Pelevanyuk, Igor Semenov, Roman Meshcheryakov Laboratory of Information Technologies Joint Institute for Nuclear Research 6 Joliot-Curie Moscow region Dubna 141980 Russia Dubna State University 19 Universitetskaya str. Moscow region Dubna 141980 Russia Institute of Nuclear Physics 1 Ibragimova str. Almaty050032 Kazakhstan Plekhanov Russian University of Economics 36 Stremyanny per Moscow117997 Russia

the JINR distributed Information and computing Environment (DICE) was created to combine resources for solving common scientific tasks, as well as to distribute peak loads across the resources of partner organizations from the JINR Member States. To monitor the hardware resources and services of the growing DICE infrastructure, a system based on Prometheus and thanos was designed and deployed. the collected metrics, including the geographical location of the JINR DICE participants, are visualized using Grafana. Software distribution is carried out with the help of the CERN Virtual Machines File System. All these topics, as well as challenges and possible overcomes, are covered in detail. © 2021 CEUR-WS. All rights reserved.

关键词： Ceph Cloud computing Cloud integration DIRAC OpenNebula

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USING distributed CLOUDS for SCIENTIFIC computing 9

USING DISTRIBUTED CLOUDS for SCIENTIFIC COMPUTING

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9th international conference "distributed computing and Grid Technologies in Science and Education", GRID 2021

作者： Kutovskiy, Nikolay Pelevanyuk, Igor Zaborov, Dmitry Joint Institute for Nuclear Research 6 Joliot-Curie St. Dubna Moscow Region 141980 Russia Institute for Nuclear Research Russian Academy of Sciences 7a 60-letiya Oktyabrya Prospekt Moscow117312 Russia Plekhanov Russian University of Economics 36 Stremyanny Lane Moscow117997 Russia

Nowadays, cloud resources are the most flexible tool to provide access to infrastructures for establishing services and applications. However, it is also a valuable resource for scientific computing. At the Joint Institute for Nuclear Research, the computing cloud was integrated with the DIRAC system. It allowed for the submission of scientific computing jobs directly to the cloud. thanks to the experience, the cloud resources of several organizations from the JINR Member States were integrated in the same way. It increased the total amount of cloud resources accessible in a uniform way through DIRAC, in the scope of the so-called distributed Information and computing Environment (DICE). Folding@Home tasks related to the SARS-CoV-2 virus were submitted to all available cloud resources. In addition to useful scientific results, such experience was also helpful in obtaining information about the performance, limitations, strengths, and weaknesses of the combined system. Based on the gained experience, the DICE infrastructure was tuned to successfully perform real user jobs related to Monte-Carlo simulation for the Baikal-GVD experiment. Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Monte Carlo methods

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Reliability Measurement Of Vehicle Sensor Data Based On Historical Perception

Reliability Measurement Of Vehicle Sensor Data Based On Hist...

引用

IEEE international conference on Data Science in Cyberspace (DSC)

作者： Chenqing Guo Jinxin Zuo Yueming Lu Weixuan Xie School of Cyberspace Security Key Lab of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

On-board sensors are utilized for monitoring and collecting a diverse range of data pertaining to the vehicle and its surroundings. However, in the field of Internet of Vehicles, security threats encountered by vehicle sensors often result in compromised accuracy of collected data. therefore, it is crucial to investigate trusted measurement methods for vehicle sensor data. this paper proposes a reliable measurement approach for vehicle sensor data based on historical perception. the method initially achieves historical feature extraction through time correlation of single sensor sequence data and spatial correlation of multisensor data. Subsequently, a reliability measurement method is devised to quantify real-time data reliability by assessing the deviation from the theoretical expected value. Finally, historical data reliability is integrated with real-time data reliability to enhance accuracy of the overall reliability measurement process. this approach takes into consideration spatio-temporal correlation of vehicle sensor data and resolves issues stemming from unbalanced datasets that lead to inaccurate evaluation results. Experimental findings demonstrate an accuracy rate of 98.91% for the proposed method.

关键词： Correlation Accuracy Reliability theory Feature extraction Real-time systems Spatial databases Sensors Security Monitoring Internet of Vehicles

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RESEARCH CLOUD computing ECOSYSTEM in Armenia 9

RESEARCH CLOUD COMPUTING ECOSYSTEM in Armenia

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9th international conference "distributed computing and Grid Technologies in Science and Education", GRID 2021

作者： Astsatryan, Hrachya Narsisian, Wahi Mirzoyan, Artashes Sahakyan, Vladimir Institute for Informatics and Automation Problems The National Academy of Sciences of the Republic of Armenia 1 Paruyr Sevak str. Yerevan0014 Armenia

Growing needs for computational resources, data storage within higher-educational institutions and the requirement for a lot of investment and financial resources the idea or the concept of "National Research Cloud Platform (NRCP)" is crucial to provide necessary IT support for educational, research and development activities, which allow access to advanced IT infrastructure, data centers, and applications and protect sensitive information. In this article we will illustrate the concept of NRCP, background, deployment stages and architecture and finally some use cases. Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Investments

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Towards a Sustainable Digital Society: Supporting Producer Mobility in Named Data networking through Immobile Anchor-Based Mechanism 9th

Towards a Sustainable Digital Society: Supporting Producer M...

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9th international conference on computing and Informatics, ICOCI 2023

作者： Abrar, Ahmad Mohd Zaini, Khuzairi Che Mohamed Arif, Ahmad Suki Omar, Mohd Hasbullah InterNetWorks Research Laboratory School of Computing Universiti Utara Malaysia UUM Sintok Kedah Sintok06010 Malaysia

ISBN: (纸本)9789819995882

the increasing proliferation of intelligent mobile devices and the subsequent surge in data traffic have placed a burden on the current Internet infrastructure. To address this challenge, Named Data networking (NDN) has emerged as a promising future Internet architecture. NDN aims to address the evolving patterns of Internet traffic by providing inherent support for consumer mobility through in-network caching. this approach enhances content availability while minimizing delays. However, producer mobility in NDN raises numerous challenges, including Interest packet loss, Interest retransmission, high signalling costs, and unnecessary bandwidth consumption. this research explores and critically analyses the most widely used approaches for managing producer mobility in NDN. this paper introduces an innovative immobile anchor-based mobility mechanism designed to address the challenges associated with producer mobility in NDN. the immobile refers to the fixed nature of the anchor router, which is strategically placed within the network topology to facilitate the management of producer mobility. this immobile anchor router serves as a centralized control point for caching and redirecting Interest packets during producer handoff processes, thereby mitigating packet loss and optimizing bandwidth usage. the focal point of this novel approach is to reduce the repercussions of producer mobility on network performance. Its aim is to minimize factors like packet loss, signalling overhead, and bandwidth usage, with the ultimate goal of enhancing the overall efficiency of NDN-based networks. © 2024, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Packet loss

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Request-based forwarding strategy in vehicular named data networking 21

Request-based forwarding strategy in vehicular named data ne...

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9th international conference on Computer and Communications Management, ICCCM 2021

作者： Al-Qutwani, Majed Wang, Xingwei Yi, Bo College of Software Northeastern University Shenyang110819 China College of Computer Science and Engineering Northeastern University Shenyang110819 China

ISBN: (纸本)9781450390071

Named Data networking (NDN) is a suitable solution for addressing the scalability and efficiency of vehicular ad hoc network (VANET). Despite applying VANET in NDN (VNDN) brings several advantages, yet few challenges, such as vehicle mobility and packet broadcasting, remain in VNDN. In this study, we propose a request-based content forwarding (RBFS) design to alleviate packet broadcast and enhance VNDN performance. Each consumer broadcasts a lighter request message instead of an interest packet to ask for a specific data packet, which will enable the provider to find the corresponding interest packet with less delay and minimal network overhead. We use a dynamic strategy, in which providers can deliver the data packet to the consumer by building unicast forwarding paths. Simulation results show that RBFS improves network performance by reducing network overhead, interest satisfaction rate, and interest packet delay. © 2021 Association for computing Machinery.

关键词： NDN VNDN Content forwarding Vehicular named data network

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