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Economy-Oriented Deadline Scheduling Policy for Render System Using IaaS Cloud

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9530))

Abstract

Along with the increase of demand for high definition animation film, when the render system with local computing resources cannot supply enough resources to satisfy the user requirement for time, acquiring additional resources is necessary. The Infrastructure as a service (IaaS) Cloud offers user with computing infrastructures on-demand to be used based on the paradigm of pay-per-use, which provides extra resources with fee to extending the capacity of render system with local cluster. Consequently, the scheduling policy under the hybrid render system should consider the constraints of deadline and budget and billing policy. In this paper, an economy-oriented deadline scheduling policy is proposed, which not only guarantees the deadline for user by the way of employing resources for rendering, but also offers an economic way to hire resources from IaaS Cloud provider reasonably. The experiment with single workload and multi workloads shows that the proposed policy can finish the user’s rendering job before deadline as well as obtain approving cost efficient.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (Grant No.61202041 and No.91330117) and National High-Tech Research and Development Program of China (Grant No.2012AA01A306 and No.2014AA01A302). Computational resources have been made available on Xi’an High Performance Computing Center.

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Correspondence to Qian Li .

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Li, Q., Wu, W., Sun, Z., Wang, L., Huang, J. (2015). Economy-Oriented Deadline Scheduling Policy for Render System Using IaaS Cloud. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9530. Springer, Cham. https://doi.org/10.1007/978-3-319-27137-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-27137-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27136-1

  • Online ISBN: 978-3-319-27137-8

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