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Adaptable scheduling schemes for scientific applications on science cloud

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4 Author(s)
Seoyoung Kim ; Dept. of Comput. Sci., Sookmyung Women''s Univ., Seoul, South Korea ; Yoonhee Kim ; Naeyoung Song ; Chongam Kim

As one of IaaS (Infrastructure-as-a-Service), it is beneficial to arrange virtual machines dynamically to applications based on resource provisioning mechanism. However, it is challenging to apply scheduling scheme to utilize resources efficiently when many tasks require a lot of resources at the same time. Especially, scientific applications, which require large-scale computing resource for long term execution period, need more dynamic scheduling to occupy resource appropriately. Resource virtualization, manipulating several virtual machines (VMs) over physical resource gives good opportunities to enhance the performance of applications and resources. In this paper, we conducted experiments on adaptable scheduling schemes with scientific applications which need a lot of resources for long execution time period on cloud computing environment by distributing jobs to VMs. We provide cloud computing infrastructure by using OpenNebula virtual infrastructure engine and Haziea scheduler. Moreover, we verified the improvement of the execution time of applications and whole resource usage by scheduling VMs according to their priorities.

Published in:

Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS), 2010 IEEE International Conference on

Date of Conference:

20-24 Sept. 2010

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