Abstract

Scientific workflows are important in modern computational science and are a convenient way to represent complex computations, which are often geographically distributed among several computers. In many scientific domains, scientists use sensors (e.g., edge devices) to gather data such as CO2 level or temperature, that are usually sent to a central processing facility (e.g., a cloud). However, these edge devices are often not powerful enough to perform basic computations or machine learning inference computations and thus applications need the power of cloud platforms to generate scientific results. This work explores the execution and deployment of a complex workflow on an edge-to-cloud architecture in a use case of the detection and classification of plankton. In the original application, images were captured by cameras attached to buoys floating in Lake Greifensee (Switzerland). We developed a workflow …

Metadata

publication

2022 IEEE 18th International Conference on e-Science (e-Science), 415-416, 2022

year

2022

publication date

2022/10/11

authors

Khushi Choudhary, Nona Nersisyan, Edward Lin, Shobana Chandrasekaran, Rajiv Mayani, Loic Pottier, Angela P Murillo, Nicole K Virdone, Kerk Kee, Ewa Deelman

link

https://ieeexplore.ieee.org/abstract/document/9973659/

resource_link

https://par.nsf.gov/servlets/purl/10416257

conference

2022 IEEE 18th International Conference on e-Science (e-Science)

pages

415-416

publisher

IEEE