Squashed embedding of E-R schemas in hypercubes

We have been investigating an approach to parallel database processing based on treating Entity-Relationship (E-R) schema graphs as dataflow graphs. A prerequisite is to find appropriate embeddings of the schema graphs into a processor graph, in this case a hypercube. This paper studies a class of adjacency preserving embeddings that map a node in the schema graph into a subcube (relaxed squashed or RS embeddings) or into adjacent subcubes (relaxed extended squashed or RES embeddings) of a hypercube. The mapping algorithm is motivated by the technique used for state assignment in asynchronous sequential machines. In general, the dimension of the cube required for squashed embedding of a graph is called the weak cubical dimension or WCD of the graph. The RES embedding provides an RES-WCD of O([left ceiling]log2n[right ceiling]) for a completely connected graph, Kn, and RS embedding provides an RS-WCD of O([left ceiling]log2n[right ceiling] + [left ceiling]log2m[right ceiling]) for a completely connected bigraph, Km,n. Typical E-R graphs are incompletely connected bigraphs. An algorithm for embedding incomplete bigraphs is presented.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28651/1/0000467.pd

ITR/IM: Enabling the Creation and Use of GeoGrids for Next Generation Geospatial Information

The objective of this project is to advance science in information management, focusing in particular on geospatial information. It addresses the development of concepts, algorithms, and system architectures to enable users on a grid to query, analyze, and contribute to multivariate, quality-aware geospatial information. The approach consists of three complementary research areas: (1) establishing a statistical framework for assessing geospatial data quality; (2) developing uncertainty-based query processing capabilities; and (3) supporting the development of space- and accuracy-aware adaptive systems for geospatial datasets. The results of this project will support the extension of the concept of the computational grid to facilitate ubiquitous access, interaction, and contributions of quality-aware next generation geospatial information. By developing novel query processes as well as quality and similarity metrics the project aims to enable the integration and use of large collections of disperse information of varying quality and accuracy. This supports the evolution of a novel geocomputational paradigm, moving away from current standards-driven approaches to an inclusive, adaptive system, with example potential applications in mobile computing, bioinformatics, and geographic information systems. This experimental research is linked to educational activities in three different academic programs among the three participating sites. The outreach activities of this project include collaboration with U.S. federal agencies involved in geospatial data collection, an international partner (Brazil\u27s National Institute for Space Research), and the organization of a 2-day workshop with the participation of U.S. and international experts

XViews: XML views of relational schemas

The Mediation of Information using XML (MIX) project is a joint effort between the the San Diego Supercomputer Center (SDSC) and the Database Lab at the University of California San Diego where we are investigating the use of XML as the medium for information modeling and information interchange among heterogeneous information sources. Relational databases represent an important type of information source. In this paper, we discuss issues in providing XML document views of relational schemas. We refer to these as, XViews. We also discuss related work from a project funded by DARPA and the US Patent and Trademark Office where we investigated issues in mapping SGML document type definitions to relational schemas. The work described here reflects initial results from the above mentioned projects. 1. Introduction The Extensible Markup Language (XML) [15] facilitates a move towards viewing the Web as a large, semistructured database consisting of many autonomous sites which are modeled us..

Data Reorganization in Parallel Database Systems

Parallel database systems are suitable for use in applications with high capacity and high performance and availability requirements. The trend in such systems is to provide efficient on-line capability for performing various system administration functions such as, index creation and maintenance, backup/restore, reorganization, and gathering of statistics. For some of these functions, the on-line capability can be efficiently supported by the use of "incremental algorithms", i.e., algorithms that achieve the function in several, relatively small (i.e., less time-consuming) steps, rather than in a single, large step. Incremental algorithms ensure that only small parts of the database become inaccessible for short durations as opposed to nonincremental algorithms which may lock large portions of the database or the entire database for a longer duration. In this paper, we discuss issues in providing concurrent data reorganization capability using incremental algorithms in parallel databa..