Gibson, Ryan M.

Lawal, Kelvin N.

Olaniyi, Titus K.

English

The exponential growth of smart Internet of Things (IoT) devices has led to an increase in data generation, transfer, storage, and management within IoT infrastructures. Consequently, there is an increase in latency, network bandwidth usage and energy consumption for managing data. This paper evaluates energy efficiency improvements through extending the traditional Cloud computing continuum with the introduction of the Fog computing paradigm. Using proof of concept (PoC), this research addresses some of the challenges with traditional cloud computing such as high energy consumption with network simulation toolsets. An evaluation was conducted to determine the best suited network simulation software tool for critically analysing Fog computing and traditional Cloud computing in terms of data management, planning and energy efficiency. This paper demonstrates a reduction in energy consumption with the introduction of Fog computing layer technologies when compared to traditional Cloud computing architecture through the iFogSim network simulation toolset. Furthermore, the differences in energy consumption and data management with Fog and Cloud computing data centres are explored

ResearchOnline@GCU

Fog computing infrastructure simulation toolset review for energy estimation, planning and scalability

https://researchonline.gcu.ac.uk/files/50326100/Lawal_K.N._et_al_2021_Fog_computing_infrastructure_simulation_toolset_review_for_energy_estimation_planning_and_scalability.pdf

Fog computing infrastructure simulation toolset review for energy estimation, planning and scalability

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ResearchOnline@GCU