Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39360
Title: Data declustering with replications
Authors: Liu, Y.
Sung, S.Y. 
Xiong, H.
Ng, P.
Issue Date: 2004
Source: Liu, Y.,Sung, S.Y.,Xiong, H.,Ng, P. (2004). Data declustering with replications. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2973 : 682-693. ScholarBank@NUS Repository.
Abstract: Declustering is used to distribute blocks of data among multiple devices, thus enabling parallel I/O access and reducing query response times. Many data declustering schemes have been proposed in the literature. However, these schemes are designed for non-replication systems, and thus they will fail if any disk fails. Assume that a single disk would fail once every five years, a non-replication system with 100 disks would have failed every 18 days. Data replication is a technique commonly used in multidisk systems to enhance availability of data during disk failures and, often as a second goal, to improve I/O performance of read-intensive applications. In this paper, we propose a LOG data declustering scheme for systems with replication. Furthermore, we present a novel replication algorithm. Although the replication algorithm is designed for the LOG declustering scheme, it is also applicable to existing schemes such as DM, GFIB, and GRS. Finally, as demonstrated by our experimental results, the LOG scheme with the proposed replication algorithm provides a significant performance improvement compared to the state-of-the-art data declustering schemes. Keywords: Parallel retrieving, data declustering, range query, replication © Springer-Verlag 2004.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/39360
ISSN: 03029743
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