Selective Replicated Declustering for Arbitrary Queries
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Divide-and-conquer scheme for strictly optimal retrieval of range queries
ACM Transactions on Storage (TOS)
Toward boosting distributed association rule mining by data de-clustering
Information Sciences: an International Journal
Generalized Optimal Response Time Retrieval of Replicated Data from Storage Arrays
ACM Transactions on Storage (TOS)
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Declustering distributes data among parallel disks to reduce retrieval cost using I/O parallelism. Many schemes were proposed for single copy declustering of spatial data. Recently, declustering using replication gained a lot of interest and several schemes with different properties were proposed. An in-depth comparison of major schemes is necessary to understand replicated declustering better. In this paper, we analyze the proposed schemes, tune some of the parameters and compare them for different query types and under different loads. We propose a three step retrieval algorithm for the compared schemes. For arbitrary queries dependent and partitioned allocation perform poorly, others perform close to each other. For range queries, they perform similarly with the exception of smaller queries in which RDA performs poorly and dependent performs well. For connected queries, partitioned allocation performs poorly and dependent performs well under light load.