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The Journal of Supercomputing

Erschienen in:

11.06.2019

IoT-F2N: An energy-efficient architectural model for IoT using Femtolet-based fog network

verfasst von: Anwesha Mukherjee, Priti Deb, Debashis De, Rajkumar Buyya

Erschienen in: The Journal of Supercomputing | Ausgabe 11/2019

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Abstract

Energy- and latency-optimized Internet of Things (IoT) is an emerging research domain within fifth-generation (5G) wireless network paradigm. In traditional cloud-centric IoT the sensor data processing and storage occurs inside remote cloud servers, which increase delay and energy consumption. To reduce the delay and energy consumption, an IoT paradigm is proposed using 5G device Femtolet-based fog network. In this architecture, the data obtained from sensors are processed and maintained inside the edge and fog devices. The Femtolet works as an adaptable fog device and it expands and shrinks coverage according to user’s presence. A mathematical model is developed for the proposed paradigm. The delay and power consumption in the proposed model are determined. Qualnet 7 is used for simulating the proposed model. The results of simulation illustrate that the proposed architectural model reduces the energy consumption and delay by approximately 25% and 43% respectively than the fog computing-based existing IoT paradigm. The comparative analysis with the existing IoT paradigm shows that IoT using Femtolet-based fog network is a green and efficient approach.

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Titel: IoT-F2N: An energy-efficient architectural model for IoT using Femtolet-based fog network
verfasst von: Anwesha Mukherjee
Priti Deb
Debashis De
Rajkumar Buyya
Publikationsdatum: 11.06.2019
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 11/2019
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-019-02928-0

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