Building Model as a Service to support geosciences

Zhenlong Li, Chaowei Yang, Qunying Huang, Kai Liu, Min Sun, Jizhe Xia

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Modeling is a fundamental methodology for simulating the past, understanding the present and predicting the future of the geospatial systems and phenomena. However, modeling in the geospatial science poses several challenges, including complex model setup, repetition in model setup, requirement for large, scalable computing resources, and management of a large amount of model output. To address these challenges, we propose Model as a Service (MaaS) by leveraging the latest advancement of cloud computing. MaaS enables various geoscience models to be published as services, and these services can be accessed through a simple web interface. MaaS automates the processes of configuring machines, setting up and running models, and managing model outputs. The computing resources are automatically provisioned by MaaS in a cloud environment. A proof-of-concept MaaS prototype is presented using a global climate change model (ModelE). Experimental results show that the MaaS prototype significantly simplifies model setup, accelerates model simulation and enhances model output by providing a web-based, on-demand, scalable modeling environment.

Original languageEnglish (US)
Pages (from-to)141-152
Number of pages12
JournalComputers, Environment and Urban Systems
Volume61
DOIs
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Ecological Modeling
  • General Environmental Science
  • Urban Studies

Cite this