Efficient storage and retrieval of multi-attribute datasets has become one of the essential requirements for many data-intensive applications. The Cartesian product file has been known as an effective multi-attribute file structure for partial-match and best-match queries. Several heuristic methods have been developed to decluster Cartesian product files over multiple disks to obtain high perfo...

The main purpose of this paper was to, for the first time, analyse spatiotemporal features background seismicity Northern Algeria and its vicinity, as identified by different declustering methods (specifically: Gardner Knopoff, Gruenthal, Uhrhammer, Reasenberg, Nearest Neighbour, Stochastic Declustering methods). Each method identifies a declustered catalogue, namely subset earthquake catalogue...

Efficient storage and retrieval of multiattribute data sets has become one of the essential requirements for many data-intensive applications. The Cartesian product file has been known as an effective multiattribute file structure for partial-match and best-match queries. Several heuristic methods have been developed to decluster Cartesian product files across multiple disks to obtain high perf...

Clusters of computers are used in large scale server sites recently, because of their good scalability and cost/performance ratio. In addition, Storage Area Network (SAN) is introduced in order to consolidate back end of such systems. I/O-bottleneck is serious problem in such an environment, because some important data-intensive applications often access part of data concurrently and repeatedly...

Several declustering functions for distributing multi-attribute data on a set of disks have been proposed in recent years. Since these functions map grid regions to disks in a static way, performance deteriorates in case of dynamic datasets and/or non-stationary data distributions. In this paper we first analyze how declustering functions can be extended in order to deal with dynamic datasets w...