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

Demetris Trihinas; Lauritz Thamsen; Jossekin Beilharz; Moysis Symeonides

doi:10.1109/IC2E55432.2022.00011

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

Demetris Trihinas
, Lauritz Thamsen
, Jossekin Beilharz
, Moysis Symeonides

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	29-35
Number of pages	7
ISBN (Electronic)	9781665491150
DOIs	https://doi.org/10.1109/IC2E55432.2022.00011
Publication status	Published - 2022
Event	10th IEEE International Conference on Cloud Engineering, IC2E 2022 - Pacific Grove, United States Duration: 26 Sept 2022 → 30 Sept 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022

Conference

Conference	10th IEEE International Conference on Cloud Engineering, IC2E 2022
Country/Territory	United States
City	Pacific Grove
Period	26/09/22 → 30/09/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Edge Computing
Energy Modeling
Internet of Things
Machine Learning
Software Testing

Access to Document

10.1109/IC2E55432.2022.00011

Cite this

Trihinas, D., Thamsen, L., Beilharz, J., & Symeonides, M. (2022). Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. In Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022 (pp. 29-35). (Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IC2E55432.2022.00011

Trihinas, Demetris ; Thamsen, Lauritz ; Beilharz, Jossekin et al. / Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 29-35 (Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022).

@inproceedings{dfea9b45b7cc4190a7141bfb063de123,

title = "Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services",

abstract = "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.",

keywords = "Edge Computing, Energy Modeling, Internet of Things, Machine Learning, Software Testing",

author = "Demetris Trihinas and Lauritz Thamsen and Jossekin Beilharz and Moysis Symeonides",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 10th IEEE International Conference on Cloud Engineering, IC2E 2022 ; Conference date: 26-09-2022 Through 30-09-2022",

year = "2022",

doi = "10.1109/IC2E55432.2022.00011",

language = "English",

series = "Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "29--35",

booktitle = "Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022",

}

Trihinas, D, Thamsen, L, Beilharz, J & Symeonides, M 2022, Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. in Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022. Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022, Institute of Electrical and Electronics Engineers Inc., pp. 29-35, 10th IEEE International Conference on Cloud Engineering, IC2E 2022, Pacific Grove, United States, 26/09/22. https://doi.org/10.1109/IC2E55432.2022.00011

Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. / Trihinas, Demetris; Thamsen, Lauritz; Beilharz, Jossekin et al.
Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 29-35 (Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services

AU - Trihinas, Demetris

AU - Thamsen, Lauritz

AU - Beilharz, Jossekin

AU - Symeonides, Moysis

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Edge Computing

KW - Energy Modeling

KW - Internet of Things

KW - Machine Learning

KW - Software Testing

UR - https://www.scopus.com/pages/publications/85143131415

U2 - 10.1109/IC2E55432.2022.00011

DO - 10.1109/IC2E55432.2022.00011

M3 - Conference contribution

AN - SCOPUS:85143131415

T3 - Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022

SP - 29

EP - 35

BT - Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th IEEE International Conference on Cloud Engineering, IC2E 2022

Y2 - 26 September 2022 through 30 September 2022

ER -

Trihinas D, Thamsen L, Beilharz J, Symeonides M. Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. In Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 29-35. (Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022). doi: 10.1109/IC2E55432.2022.00011

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this