an energy-aware resource allocation method for scientific workflow executions in cloud environment

Xiaolong Xu*, Wanchun Dou, Xuyun Zhang, Jinjun Chen

*Corresponding author for this work

Research output: Contribution to journalArticle

91 Citations (Scopus)


Scientific workflows are often deployed across multiple cloud computing platforms due to their large-scale characteristic. This can be technically achieved by expanding a cloud platform. However, it is still a challenge to conduct scientific workflow executions in an energy-aware fashion across cloud platforms or even inside a cloud platform, since the cloud platform expansion will make the energy consumption a big concern. In this paper, we propose an Energy-aware Resource Allocation method, named EnReal, to address the above challenge. Basically, we leverage the dynamic deployment of virtual machines for scientific workflow executions. Specifically, an energy consumption model is presented for applications deployed across cloud computing platforms, and a corresponding energy-aware resource allocation algorithm is proposed for virtual machine scheduling to accomplish scientific workflow executions. Experimental evaluation demonstrates that the proposed method is both effective and efficient.

Original languageEnglish
Pages (from-to)166-179
Number of pages14
JournalIEEE Transactions on Cloud Computing
Issue number2
Publication statusPublished - 2016
Externally publishedYes


  • Energy-aware method
  • resource allocation
  • scientific workflow
  • cloud computing

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