Paper Info
Title
A Virtualization-Based Hybrid Storage System For A Map-Reduce Framework
Abstract
A map-reduce framework is popular for big data analysis. In the typical map-reduce framework, both master node and worker nodes can use hard-disk drives ( HDDs) as local disks for the map-reduce computation. However, because of the inherit mechanical problems of HDDs, the I/O performance is a bottleneck for the map-reduce framework when I/O-intensive applications ( e.g., sorting) are performed. Replacing HDDs with solid-state drives ( SSDs) is not economical, although SSDs have better performance than HDDs. In this paper, we propose a virtualization-based hybrid storage system for the map-reduce framework. The objective of the paper is to combine the advantages of the fast access property of SSDs and the low cost of HDDs by realizing an economical design and improving I/O performance of a map-reduce framework in a virtualization environment. We propose three storage combinations: SSD-based, HDD-based, and a hybrid of SSD-based and HDD-based storage systems which balances speed, capacity, and lifetime. According to experiments, the hybrid of SSD-based and HDD-based storage systems offers superior performance and economy.
Year
DOI
Venue
2016
10.1587/transinf.2015EDP7365
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Keywords
Field
DocType
virtualization, hybrid storage systems, map-reduce, solid-state drives
Virtualization,Converged storage,EMC Invista,Computer science,Hybrid storage system,Operating system,Embedded system
Journal
Volume
Issue
ISSN
E99D
9
1745-1361
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Aseffa Dereje Tekilu100.68
Chin-Hsien Wu241947.93