The Eighth International Conference on Green Communications, Computing and Technologies

GREEN 2023

September 25, 2023 to September 29, 2023 - Porto, Portugal

Deadlines

Submission

Aug 01, 2023

Notification

Aug 20, 2023

Registration

Sep 05, 2023

Camera ready

Sep 05, 2023

Deadlines differ for special tracks. Please consult the conference home page for special tracks Call for Papers (if any).

Publication

Published by IARIA Press (operated by Xpert Publishing Services)

Archived in the Open Access IARIA ThinkMind Digital Library

Prints available at Curran Associates, Inc.

Authors of selected papers will be invited to submit extended versions to a IARIA Journal

Indexing Procedure

Affiliated Journals

GREEN 2023 - The Eighth International Conference on Green Communications, Computing and Technologies

September 25, 2023 - September 29, 2023

GREEN 2023: Awards
Due to multiple requests, the submission deadline has been moved.
Onsite and Online Options: In order to accommodate a large number of situations, we are offering the option for either physical presence or virtual participation (pdf slides or pre-recorded videos).

The papers listed below have been selected as "Best Papers" based on the reviews of the original submission, the camera-ready version, and the presentation during the conference. For the awarded papers, a digital award will be issued in the name of the authors. The authors of these papers are also receiving invitations to submit an extended article version to one of the IARIA Journals.

 

Awarded Papers (also Invited for IARIA Journals)

Comparable Machine Learning Efficiency: Balanced Metrics for Natural Language Processing
Daniel Schönle, Christoph Reich, Djaffar Ould Abdeslam

 

The following papers have been selected on the basis of their contents, specificaly for lending themselves to an interesting extended work. The authors of these papers are receiving invitations to submit an extended article version to one of the IARIA Journals.

Papers Invited for IARIA Journals

Cost and Carbon Reduction for Microsoft Azure Virtual Machines Using Workload Analysis
Daisy Wong, Oliver Zhang, Jacky Huang

Reducing Carbon Footprint of AI Models Without Compromising Performance
Austin Deng, Xingzhi Huang, Michael Lu

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