Multidimensional routing indices for efficient distributed query processing

Abstract

Traditional routing indices in peer-to-peer (P2P) networks are mainly designed for document retrieval applications and maintain aggregated one-dimensional values representing the number of documents that can be obtained in a certain direction in the network. In this paper, we introduce the concept of multidimensional routing indices (MRIs), which are suitable for handling multidimensional data represented by minimum bounding regions (MBRs). Depending on data distribution on peers, the aggregation of the MBRs may lead to MRIs that exhibit extremely poor performance, which renders them ineffective. Thus, focusing on a hybrid unstructured P2P network, we analyze the parameters for building MRIs of high selectivity. We present techniques that boost the query routing performance by detecting similar peers and grouping and reassigning these peers to other parts of the hybrid network in a distributed and scalable way. We demonstrate the advantages of our approach using largescale simulations.