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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 9 > No. 2L

 
   

I/O Characteristics and Implications of Big Data Processing on Virtualized Environments

PP: 591-598
Author(s)
Sewoog Kim, Dongwoo Kang, Jongmoo Choi,
Abstract
In this paper, I/O characteristics of data-intensive applications running on virtualized environments are explored. It is observed that virtual machines have a tendency to request I/Os in a bursty manner. Also, I/Os are triggered by several virtual machines at the same time. These concurrent and bursty I/Os cause the interference among virtual machines such as frequent context switches and long seek distances, which eventually deteriorates I/O performance significantly. To overcome this problem, a novel burstiness-aware I/O scheduler is proposed, which consists of three components: burstiness detector, coarse-grained dispatcher and starvation handler. The key idea of the proposed scheduler is detecting bursty virtual machines on-line and allowing a detected machine to consume most of disk bandwidth exclusively for a given time quantum to reduce the interference. In addition, it provides long-term fairness while avoiding starvation. Performance evaluation based on implementation shows that the proposed scheduler can improve the execution time and I/O throughput of the three real workloads by decreasing the number of context switches and seek distances.

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