Metecloud: Meteorological cloud computing platform for mobile weather forecasts based on energy-aware scheduling

Wei Fang, Victor S. Sheng, Xue Zhi Wen

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Nowadays, more and more large-scale data intensive applications such as meteorological big data executed in data centers require a huge amount of electrical energy and energy costs. Therefore, minimizing the energy consumption and reducing the environmental impact is our goal of Green Cloud Computing. In this paper, a new meteorological cloud computing platform (MeteCloud) for Mobile Weather Forecasts based on energy-aware scheduling for improving the energy efficiency is proposed. This approach is different from the existing researches, which wants to emphasize the importance of energy consumption in the study of constructing cloud computing platform for meteorological applications. And, a novel MeteCloud architecture and a hybrid scheduling algorithm are given to testify the availability of meteorological cloud computing platform. Finally, the experimental results demonstrate that MeteCloud has better performance and efficiency.

Original languageEnglish
Pages (from-to)959-967
Number of pages9
JournalJournal of Internet Technology
Volume19
Issue number3
DOIs
StatePublished - 2018

Keywords

  • Energy-aware scheduling
  • MapReduce
  • MeteCloud
  • Meteorological cloud computing

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