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CORDIS - EU research results
CORDIS

Devise & explore a novel approach for energy consumption and carbon footprint reduction of ICT services in the era of next-generation mobile telecommunications (6G)

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Energy Consumption Ecosystem (opens in new window)

This deliverable captures the results from T1.1 and documents the value chain for the energy consumption and carbon footprint ecosystem. It also describes the possible impact on the relevant regulations.

Dissemination and Communication Plan (opens in new window)

Document showcasing the different initiatives to output the different outcomes of the project and how to foment reachability towards intended target audiences.

Draft Functional Architecture (opens in new window)

This deliverable describes the overall draft system architecture for monitoring and controlling the end-to-end energy consumption and carbon footprint. This deliverable is on M15 while the end version of the deliverable with the final project results is on M30. This Deliverable is also input for the work in WP2, WP3 and WP4

Assessment Plan (opens in new window)

Identifies the mechanisms and technologies that will be assessed, a how that assessment will be made.

Data Management Plan (opens in new window)

The DMP contains detailed procedures for all data types produced during the project

Publications

Sustainable Mobile System: Data for Balancing Network Performance and Energy Consumption

Author(s): Janez Sterle, Luka Koršič, Rudolf Sušnik
Published in: 2024
Publisher: Slovensko društvo za elektronske komunikacije

Carbon-Aware Full-Decentralized Edge Computing Peer Offloading for Multiple Providers

Author(s): H. R. Chi, D. Corujo, R. L. Aguiar
Published in: 2024
Publisher: IEEE

FedZero: Leveraging Renewable Excess Energy in Federated Learning (opens in new window)

Author(s): P. Wiesner, R. Khalili, D. Grinwald, P. Agrawal, L. Thamsen, O. Kao
Published in: E-Energy, 2024
Publisher: ACM
DOI: 10.1145/3632775.3639589

Train Once Apply Anywhere: Effective Scheduling for Network Function Chains Running on FUMES

Author(s): M. Blöcher, N. Nedderhut, P. Chuprikov, R. Khalili, P. Eugster, L. Wang
Published in: 2024
Publisher: IEEE

A Safe Deep Reinforcement Learning Approach for Energy Efficient Federated Learning in Wireless Communication Networks

Author(s): N. Koursioumpas, L. Magoula, N. Petropouleas, A.-I. Thanopoulos, T. Panagea, N. Alonistioti, MA Gutierrez-Estevez, R. Khalili
Published in: 2024, ISSN 2473-2400
Publisher: IEEE

Standardization Roadmap towards Sustainable 6G

Author(s): Sripriya Srikant Adhatarao, Zoran Despotovic, Ljupco Jorguseski, Ewout Brandsma, Daniel Corujo, Artur Hecker
Published in: 2024
Publisher: IEEE

European Vision for the 6G Network Ecosystem (opens in new window)

Author(s): Uusitalo, Mikko; Bernardos, Carlos Jesus; Kaloxylos, Alexandros; Bourse, Didier Arnaud; Norp, Toon; Lønsethagen, Håkon; Hecker, Artur; Rugeland, Patrik; Papagianni, Chrysa; Bulakci, Ömer; Li, Xi; Ericson, Mårten; Anton-Haro, Carles; Massod Khorsandi, Bahare; Ramos-Lopez, Aurora; Frascolla, Valerio; Marco, Gramaglia; Gavras, Anastasius; Trichias, Konstantinos
Published in: 2024
Publisher: Zenodo
DOI: 10.5281/ZENODO.14230482

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