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An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures. / Bozorgchenani, Arash; Tarchi, Daniele; Emanuele Corazza, Giovanni.
GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE Publishing, 2018.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Bozorgchenani, A, Tarchi, D & Emanuele Corazza, G 2018, An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures. in GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE Publishing. https://doi.org/10.1109/GLOCOM.2017.8254703

APA

Bozorgchenani, A., Tarchi, D., & Emanuele Corazza, G. (2018). An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures. In GLOBECOM 2017 - 2017 IEEE Global Communications Conference IEEE Publishing. https://doi.org/10.1109/GLOCOM.2017.8254703

Vancouver

Bozorgchenani A, Tarchi D, Emanuele Corazza G. An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures. In GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE Publishing. 2018 doi: 10.1109/GLOCOM.2017.8254703

Author

Bozorgchenani, Arash ; Tarchi, Daniele ; Emanuele Corazza, Giovanni. / An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures. GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE Publishing, 2018.

Bibtex

@inproceedings{48bbb1f6437744769308db414b4281c4,
title = "An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures",
abstract = "Fog computing is a fascinating paradigm which has drawn attention recently by bringing the cloud capabilities closer to the users. A fog computing infrastructure can be seen as composed by two layers: one including Fog Nodes (FNs) and another the Fog Access Points (F-APs). While FNs are usually battery operated, the F-APs are instead connected to the electrical networks having unlimited energy. Moreover, F-APs facilitate the computation of tasks due to their higher storage and computational capabilities compared to the FNs. Considering FN energy consumption and task processing delay, we propose a suboptimal partial offloading technique aiming at exploiting jointly both FNs and F-APs. The simulation results demonstrate how partial offloading has a profound impact on the network lifetime and reduces energy consumption and task processing delay by comparing the single and two layer architectures.",
author = "Arash Bozorgchenani and Daniele Tarchi and {Emanuele Corazza}, Giovanni",
year = "2018",
month = jan,
day = "15",
doi = "10.1109/GLOCOM.2017.8254703",
language = "English",
isbn = "9781509050208",
booktitle = "GLOBECOM 2017 - 2017 IEEE Global Communications Conference",
publisher = "IEEE Publishing",

}

RIS

TY - GEN

T1 - An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures

AU - Bozorgchenani, Arash

AU - Tarchi, Daniele

AU - Emanuele Corazza, Giovanni

PY - 2018/1/15

Y1 - 2018/1/15

N2 - Fog computing is a fascinating paradigm which has drawn attention recently by bringing the cloud capabilities closer to the users. A fog computing infrastructure can be seen as composed by two layers: one including Fog Nodes (FNs) and another the Fog Access Points (F-APs). While FNs are usually battery operated, the F-APs are instead connected to the electrical networks having unlimited energy. Moreover, F-APs facilitate the computation of tasks due to their higher storage and computational capabilities compared to the FNs. Considering FN energy consumption and task processing delay, we propose a suboptimal partial offloading technique aiming at exploiting jointly both FNs and F-APs. The simulation results demonstrate how partial offloading has a profound impact on the network lifetime and reduces energy consumption and task processing delay by comparing the single and two layer architectures.

AB - Fog computing is a fascinating paradigm which has drawn attention recently by bringing the cloud capabilities closer to the users. A fog computing infrastructure can be seen as composed by two layers: one including Fog Nodes (FNs) and another the Fog Access Points (F-APs). While FNs are usually battery operated, the F-APs are instead connected to the electrical networks having unlimited energy. Moreover, F-APs facilitate the computation of tasks due to their higher storage and computational capabilities compared to the FNs. Considering FN energy consumption and task processing delay, we propose a suboptimal partial offloading technique aiming at exploiting jointly both FNs and F-APs. The simulation results demonstrate how partial offloading has a profound impact on the network lifetime and reduces energy consumption and task processing delay by comparing the single and two layer architectures.

U2 - 10.1109/GLOCOM.2017.8254703

DO - 10.1109/GLOCOM.2017.8254703

M3 - Conference contribution/Paper

SN - 9781509050208

BT - GLOBECOM 2017 - 2017 IEEE Global Communications Conference

PB - IEEE Publishing

ER -