A novel transversal processing model to build environmental big data services in the cloud Articles uri icon

authors

  • Barrón Lugo, Juan Armando
  • GONZALEZ COMPEAN, JOSE LUIS
  • CARRETERO PEREZ, JESUS
  • LOPEZ AREVALO, IVAN
  • MONTELLA, RAFFAELE

publication date

  • October 2021

start page

  • 1

end page

  • 17

issue

  • 105173

volume

  • 144

International Standard Serial Number (ISSN)

  • 1364-8152

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.

subjects

  • Computer Science

keywords

  • big data; cloud computing; environmental data; climate data; machine learning; data analytic