Paper Info
Title
A novel transversal processing model to build environmental big data services in the cloud
Abstract
This paper presents a novel transversal, agnostic-infrastructure, and generic processing model to build environmental big data services in the cloud. Transversality is used for building processing structures (PS) by reusing/coupling multiple existent software for processing environmental monitoring, climate, and earth observation data, even in execution time, with datasets available in cloud-based repositories. Infrastructure-agnosticism is used for deploying/executing PSs on/in edge, fog, and/or cloud. Genericity is used to embed analytic, merging information, machine learning, and statistic micro-services into PSs for automatically and transparently converting PSs into big data services to support decision-making procedures. A prototype was developed for conducting case studies based on the data climate classification, earth observation products, and making predictions of air data pollution by merging different monitoring climate data sources. The experimental evaluation revealed the efficacy and flexibility of this model to create complex environmental big data services.
Year
DOI
Venue
2021
10.1016/j.envsoft.2021.105173
Environmental Modelling & Software
Keywords
DocType
Volume
Big data,Cloud computing,Environmental data,Climate data,Machine learning,Data analytic
Journal
144
ISSN
Citations 
PageRank 
1364-8152
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
J. Armando Barron-Lugo100.34
José Luis González Compeán200.34
Jesus Carretero323929.04
Ivan López-arévalo42914.56
Raffaele Montella500.34