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Published in: Arabian Journal for Science and Engineering 11/2019

29-06-2019 | Research Article - Computer Engineering and Computer Science

Storage Node Allocation Methods for Erasure Code-based Cloud Storage Systems

Authors: Ojus Thomas Lee, G. J. Akash, S. D. Madhu Kumar, Priya Chandran

Published in: Arabian Journal for Science and Engineering | Issue 11/2019

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Abstract

Erasure codes, in the recent past, have emerged as an alternative to data replication-based systems for storing big data. Efficient choice of code and data nodes from the numerous available storage nodes is the key to the performance of any storage system. This paper presents the Storage Node Allocation Problem for selecting the suitable set of nodes for holding data and code blocks by representing the storage systems as a complete bipartite graph. Additionally, the paper formally proves that the problem is NP-hard and proposes approximate solutions using greedy, ant colony optimization and clustering-based methods. The solutions accomplish efficient choice of storage nodes by utilizing parameters like bandwidth availability, distance between the nodes, computational load and disk space availability.

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Footnotes
1
The number of storage nodes in the data center in our consideration is \(>= 10,000\), which we virtually partition as \(m >= 5000\) and \(y >= 5000\). The number of storage nodes to be allocated depends on the code RS(xy) and as an example for RS(10,8), the values \(x = 10\) and \(y = 8\).
 
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Metadata
Title
Storage Node Allocation Methods for Erasure Code-based Cloud Storage Systems
Authors
Ojus Thomas Lee
G. J. Akash
S. D. Madhu Kumar
Priya Chandran
Publication date
29-06-2019
Publisher
Springer Berlin Heidelberg
Published in
Arabian Journal for Science and Engineering / Issue 11/2019
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-019-03983-8

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