Translational Edge and Cloud Computing to Advance Lake Water Quality Forecasting

TR Number

Date

2024-11-20

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Abstract

In this article, we report on our experiences with interdisciplinary projects at the intersection of freshwater ecology, data science, and computer science. The translational research process has progressively led to the development of distributed systems that apply both edge computing and function-as-a-service (FaaS) cloud computing to support end-to-end water quality forecasting workflows across the edge-to-cloud continuum.

Description

Keywords

Cloud computing, Collaboration, Forecasting, Lakes, Next generation networking, Prototypes, Training, Translational research, Water quality

Citation