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An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing architectures
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.
An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing architectures
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.
An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing architectures
BOZORGCHENANI, ARASH (Autor:in) / TARCHI, DANIELE (Autor:in) / CORAZZA, GIOVANNI EMANUELE (Autor:in) / Arash, Bozorgchenani / Daniele, Tarchi / Giovanni Emanuele Corazza
01.01.2017
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
DDC:
690
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