| Title | A Federated Fog-Cloud Framework for Data Processing and Orchestration: A Case Study in Smart Cities |
|---|---|
| ID_Doc | 40995 |
| Authors | Lan, DP; Liu, Y; Taherkordi, A; Eliassen, F; Delbruel, S; Lei, L |
| Title | A Federated Fog-Cloud Framework for Data Processing and Orchestration: A Case Study in Smart Cities |
| Year | 2021 |
| Published | |
| 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. |
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