Efficient processing of nearest neighbor queries in parallel multimedia databases

Abstract

This paper deals with the performance problem of nearest neighbor queries in voluminous multimedia databases. We propose a data allocation method which allows achieving a query processing time in parallel settings. Our proposal is based on the complexity analysis of content based retrieval when it is used a clustering method. We derive a valid range of values for the number of clusters that should be obtained from the database. Then, to efficiently process nearest neighbor queries, we derive the optimal number of nodes to maximize parallel resources. We validated our method through experiments with different high dimensional databases and implemented a query processing algorithm for full k nearest neighbors in a shared nothing cluster. © 2008 Springer-Verlag Berlin Heidelberg.