Applications that require a high degree of distribution and
loosely-coupled connectivity are ubiquitous in various domains,
including scientific databases, bioinformatics, and multimedia
retrieval. In all these applications, data is typically voluminous and
multidimensional, and support for advanced query operators is required
for effective querying and efficient processing. To address this
challenge, we adopt a hybrid P2P architecture and propose novel indexing
and query processing algorithms. We present a scalable framework that
relies on data summaries that are distributed and maintained as
multidimensional routing indices. Different types of data summaries
enable efficient processing of a variety of advanced query operators.