A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2009; you can also visit the original URL.
The file type is
We propose a method to achieve declustering for cartesian product les on M units. The focus is on range queries, as opposed to partial match queries that older declustering methods have examined. Our method uses a distance-preserving mapping, namely, the Hilbert curve, to impose a linear ordering on the multidimensional points (buckets); then, it traverses the buckets according to this ordering, assigning buckets to disks in a round-robin fashion. Thanks to the good distance-preservingdoi:10.1109/pdis.1993.253077 dblp:conf/pdis/FaloutsosB93 fatcat:3ujcndpl5jhnrioxhmcdlegtky