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Title	A Federated Fog-Cloud Framework For Data Processing And Orchestration: A Case Study In Smart Cities
ID_Doc	1661
Authors	Lan D.; Liu Y.; Taherkordi A.; Eliassen F.; Delbruel S.; Lei L.
Year	2021
Published	Proceedings of the ACM Symposium on Applied Computing
DOI	http://dx.doi.org/10.1145/3412841.3444962
Abstract	The fog computing paradigm has been proposed to alleviate the pressures on cloud platforms for data processing and enable computation-intensive and delay-sensitive applications in smart cities. However, state-of-the-art approaches mainly advocate either cloud-or fog-based data processing solutions, and they also lack a common framework for programming over the fog-cloud continuum. In this paper, we propose a distributed, fog-cloud data processing and orchestration framework, which is capable of exploiting the semantics of both fog platforms and the Cloud. Our framework can create on-demand process engine data flow (PEDF) spanning multiple device layers with various resource constraints. This will considerably help the developers rapidly develop and deploy data processing applications over the fog-cloud continuum. Our proposed framework is validated in a real-world scenario - -IoT data streaming analytics for the smart green wall in a smart city - -which demonstrates efficient resource usage and latency reduction. © 2021 ACM.
Author Keywords	cloud computing; data processing; fog computing; orchestration; smart city

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