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Evaluating I/O Scheduler in Virtual Machines for Mapreduce Application

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4 Author(s)
Jun Fang ; Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China ; Shoubao Yang ; Wenyu Zhou ; Hu Song

This paper explores the relationship between I/O scheduling in a virtual machine monitor (VMM) and performance of Map Reduce applications running on the virtual machines (VMs). Traditionally, Map Reduce applications running on the virtual machines perform worse than on the physical machines due to competing for I/O. In this paper, we discuss the effect of I/O scheduling on performance of Map Reduce running on VMs. We present two strategies to improve the I/O scheduling and evaluate the performance through experiments. The results show that the strategies could reduce the percentage of I/O waiting and time consuming of Map Reduce applications effectively.

Published in:

Grid and Cooperative Computing (GCC), 2010 9th International Conference on

Date of Conference:

1-5 Nov. 2010