29,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
  • Broschiertes Buch

The project Concurrency Control Protocol for Clipping Indexing deals with the multidimensional databases. In multidimensional indexing trees, the overlapping of nodes will tend to degrade query performance, as one single point query may need to traverse multiple branches of the tree if the query point is in an overlapped area. Multidimensional databases are beginning to be used in a wide range of applications. To meet this fast-growing demand, the R-tree family is being applied to support fast access to multidimensional data, for which the R+-tree exhibits outstanding search performance. To…mehr

Produktbeschreibung
The project Concurrency Control Protocol for Clipping Indexing deals with the multidimensional databases. In multidimensional indexing trees, the overlapping of nodes will tend to degrade query performance, as one single point query may need to traverse multiple branches of the tree if the query point is in an overlapped area. Multidimensional databases are beginning to be used in a wide range of applications. To meet this fast-growing demand, the R-tree family is being applied to support fast access to multidimensional data, for which the R+-tree exhibits outstanding search performance. To support efficient concurrent access in multi-user environments, concurrency control mechanisms for multidimensional indexing have been proposed. However, these mechanisms cannot be directly applied to the R+-tree because an object in the R+-tree may be indexed in multiple leaves. This paper proposes a concurrency control protocol for R-tree variants with object clipping, namely, Granular Locking for clipping indexing (GLIP). GLIP is the first concurrency control approach specifically designed for the R+-tree and its variants, and it supports efficient concurrent operations.
Autorenporträt
Le Dr Ravi Kanth Motupalli a obtenu son doctorat à l'université Acharya Nagarjuna et poursuit actuellement son post-doctorat. Ses domaines d'intérêt en matière de recherche sont l'analyse des données et le traitement des images.