Methodical Analysis of a Fog Computing Assisted Animal-Welfare Software System in a Real-World Smart Dairy Farm IoT Deployment

Taneja, Mohit and Jalodia, Nikita and Malone, Paul and Misha, Eyal (2021) Methodical Analysis of a Fog Computing Assisted Animal-Welfare Software System in a Real-World Smart Dairy Farm IoT Deployment. In: 7th IEEE World Forum on Internet of Things, WF-IoT 2021 :. 7th IEEE World Forum on Internet of Things, WF-IoT 2021 . Institute of Electrical and Electronics Engineers Inc., USA, pp. 857-864. ISBN 9781665444316

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Abstract

In the IoT era, the devices along the things-to-cloud continuum, present a unique opportunity to additionally serve as computing hubs. Termed Fog computing, this paradigm can be used to host applications and process data closer to the source. In this article, we present a methodical analysis of our fog enabled software system in an IoT enabled smart dairy farm. The developed software system uses locomotion data generated by wearables on cows' feet to detect anomalies in their behaviour. We analyze the benefits of using a fog computing assisted approach for developing such IoT solutions. We use resource utilization as the performance metric for analyzing the benefits of leveraging the fog computing paradigm compared to the traditional cloud centric approach. The results suggest that a fog enabled software system brings benefits such as efficient utilization of computing resources, improved QoS etc. The evaluation indicates that there will be need of special design (including both low-level and high-level system design) re-configurations and also re-engineering of some components to provide higher scalability using less computational resources.

Item Type:	Book Section
Additional Information:	Funding Information: ACKNOWLEDGMENT This work emanated from research funded by (i) SFI and DAFM on behalf of the Government of Ireland to the VistaMilk SFI Research Centre (16/RC/3835), (ii) CISCO Research Gift Fund, (iii) NGI Explorers Fellowship Grant (grant agreement no. 825183), (iv) IoF2020 which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 731884. Publisher Copyright: © 2021 IEEE.
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/1700/1702
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Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:17
Last Modified:	07 Jun 2023 18:40
URI:	http://repository-testing.wit.ie/id/eprint/5130

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