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An Efficient Scheduling of HPC Applications on Geographically Distributed Cloud Data Centers

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Computer Networks and Distributed Systems (CNDS 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 428))

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Abstract

Cloud computing provides a flexible infrastructure for IT industries to run their High Performance Computing (HPC) applications. Cloud providers deliver such computing infrastructures through a set of data centers called a cloud federation. The data centers of a cloud federation are usually distributed over the world. The profit of cloud providers strongly depends on the cost of energy consumption. As the data centers are located in various corners of the world, the cost of energy consumption and the amount of CO2 emission in different data centers varies significantly. Therefore, a proper allocation of HPC applications in such systems can result in a decrease of CO2 emission and a substantial increase of the providers’ profit. Reduction of CO2 emission also mitigates the destructive environmental impacts. In this paper, the problem of scheduling HPC applications on a geographically distributed cloud federation is scrutinized. To address the problem, we propose a two-level scheduler which is able to reach a good compromise between CO2 emission and the profit of cloud provider. The scheduler should also satisfy all HPC applications’ deadline and memory constraints. Simulation results based on a real intensive workload indicate that the proposed scheduler reduces the CO2 emission by 17 % while at the same time it improves the provider’s profit by 9 % on average.

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Author information

Authors and Affiliations

  1. School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran

    Aboozar Rajabi

  2. Mälardalen Real-Time Research Centre, Mälardalen University, Västeras, Sweden

    Hamid Reza Faragardi & Thomas Nolte

Authors
  1. Aboozar Rajabi
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  2. Hamid Reza Faragardi
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  3. Thomas Nolte
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Corresponding author

Correspondence to Aboozar Rajabi .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Sharif University of Technology, Sharif University of Technology, Tehran, Iran

    Amir Hossein Jahangir

  2. Department of Computer Engineering, Sharif University of Technology, Sharif University of Technology, Tehran, Iran

    Ali Movaghar

  3. Department of Computer Engineering, Sharif University of Technology, Sharif University of Technology, Tehran, Iran

    Hossein Asadi

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Rajabi, A., Faragardi, H.R., Nolte, T. (2014). An Efficient Scheduling of HPC Applications on Geographically Distributed Cloud Data Centers. In: Jahangir, A., Movaghar, A., Asadi, H. (eds) Computer Networks and Distributed Systems. CNDS 2013. Communications in Computer and Information Science, vol 428. Springer, Cham. https://doi.org/10.1007/978-3-319-10903-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-10903-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10902-2

  • Online ISBN: 978-3-319-10903-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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