Distributed Inference for Energy-efficient Monitoring at the Network Edge

Project Information

DIME

Grant agreement ID: 101062011

DOI

10.3030/101062011

Project closed

EC signature date 19 May 2022

Start date 1 June 2022

End date 31 May 2024

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 181 152,96

Coordinated by

FUNDACION IMDEA NETWORKS
Spain

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

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected processed or generated by the action It is a document describing what data will be collected processed or generated and following what methodology and standards whether and how this data will be shared andor made open and how it will be curated and preserved

Documents, reports (1)

Communication, Dissemination & Outreach Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Publications

Conference proceedings (3)

Improved Decision Module Selection for Hierarchical Inference in Resource-Constrained Edge Devices

Author(s): Adarsh Prasad Behera, Roberto Morabito, Joerg Widmer, and Jaya Prakash Champati
Published in: ISBN 9781450399906
Publisher: ACM
DOI: 10.1145/3570361.3615732

An Offloading Algorithm for Maximizing Inference Accuracy on Edge Device in an Edge Intelligence System

Author(s): Andrea Fresa and Jaya Prakash Champati
Published in: MSWIM '22, Issue 25TH, 2022, ISBN 9781450394826
Publisher: Association for Computing Machinery (ACM)
DOI: 10.1145/3551659.3559044

The Case for Hierarchical Deep Learning Inference at the Network Edge

Author(s): Ghina Al-Atat, Andrea Fresa, Adarsh Prasad Behera, Vishnu Narayanan Moothedath, James Gross, and Jaya Prakash Champati
Published in: ISBN 9798400702129
Publisher: ACM
DOI: 10.1145/3597062.3597278

Peer reviewed articles (2)

Getting the Best Out of Both Worlds: Algorithms for Hierarchical Inference at the Edge

Author(s): Vishnu N. Moothedath, Jaya Prakash Champati, James Gross
Published in: IEEE Transactions on Machine Learning in Communications and Networking, ISSN 2831-316X
Publisher: IEEE
DOI: 10.1109/TMLCN.2024.3366501

Offloading Algorithms for Maximizing Inference Accuracy on Edge Device in an Edge Intelligence System

Author(s): A. Fresa and J. P. Champati
Published in: IEEE Transactions on Parallel and Distributed Systems, ISSN 1045-9219
Publisher: IEEE
DOI: 10.1109/TPDS.2023.3267458