Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services

Trihinas, D., Thamsen, L., Beilharz, J. and Symeonides, M. (2022) Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, pp. 29-35. ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00011)

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Energy consumption and carbon emissions are expected to be crucial factors for Internet of Things (IoT) applications. Both the scale and the geo-distribution keep increasing, while Artificial Intelligence (AI) further penetrates the “edge” in order to satisfy the need for highly-responsive and intelligent services. To date, several edge/fog emulators are catering for IoT testing by supporting the deployment and execution of AI-driven IoT services in consolidated test environments. These tools enable the configuration of infrastructures so that they closely resemble edge devices and IoT networks. However, energy consumption and carbon emissions estimations during the testing of AI services are still missing from the current state of IoT testing suites. This study highlights important questions that developers of AI-driven IoT services are in need of answers, along with a set of observations and challenges, aiming to help researchers designing IoT testing and benchmarking suites to cater to user needs.

Item Type:Conference Proceedings
Additional Information:This work is partially supported by the University of Nicosia Seed Grant Scheme for the FlockAI project.
Glasgow Author(s) Enlighten ID:Thamsen, Dr Lauritz
Authors: Trihinas, D., Thamsen, L., Beilharz, J., and Symeonides, M.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2022 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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