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EMPYREAN: Trustworthy, Cognitive and AI-driven Collaborative Associations of IoT Devices and Edge Resources for Data Processing

Published: 30 August 2024 Publication History

Abstract

The EU-funded EMPYREAN project (empyrean-horizon.eu) aims to establish a hyper-distributed computing paradigm, leveraging collaborative, heterogeneous IoT devices and federated resources. EMPYREAN focuses on developing technologies for efficient AI workload processing, secure distributed edge storage and cloud-native application development. It will offer open and standardised APIs and use open-source platforms. EMPYREAN's capabilities will be demonstrated through three use cases: advanced manufacturing, smart agriculture, and warehouse automation.

References

[1]
IoT and 5G City, www.ngiot.eu/wp-content/uploads/sites/26/2019/07/IoT-5G-smartcity-report-NGIoT.pdf
[2]
Survey - Less Than 10% of IoT Devices Keep Data Secure, www.iotsecurityfoundation.org/survey-less-than-10-of-iot-devices-keep-data-secure
[3]
A. Kretsis, et al., "SERRANO: Transparent Application Deployment in a Secure, Accelerated and Cognitive Cloud Continuum", Workshop on Intelligent operations, security, and acceleration for edge computing (MeditCom), 2021
[4]
Alliance for IoT and Edge Computing Innovation (AIOTI) Strategic Research and Innovation Agenda (SRIA), aioti.eu/wp-content/uploads/2023/01/AIOTI-SRIA-Final.pdf

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  1. EMPYREAN: Trustworthy, Cognitive and AI-driven Collaborative Associations of IoT Devices and Edge Resources for Data Processing

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        cover image ACM Conferences
        HPDC '24: Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing
        June 2024
        436 pages
        ISBN:9798400704130
        DOI:10.1145/3625549
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        New York, NY, United States

        Publication History

        Published: 30 August 2024

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        Author Tags

        1. edge
        2. cloud
        3. IoT
        4. AI
        5. associations

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