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On the evaluation of exact-match and range queries over multidimensional data in distributed hash tables

Date

2012

Authors

Malensek, Matthew, author
Pallickara, Shrideep, advisor
Draper, Bruce, committee member
Randall, David, committee member

Journal Title

Journal ISSN

Volume Title

Abstract

The quantity and precision of geospatial and time series observational data being collected has increased alongside the steady expansion of processing and storage capabilities in modern computing hardware. The storage requirements for this information are vastly greater than the capabilities of a single computer, and are primarily met in a distributed manner. However, distributed solutions often impose strict constraints on retrieval semantics. In this thesis, we investigate the factors that influence storage and retrieval operations on large datasets in a cloud setting, and propose a lightweight data partitioning and indexing scheme to facilitate these operations. Our solution provides expressive retrieval support through range-based and exact-match queries and can be applied over massive quantities of multidimensional data. We provide benchmarks to illustrate the relative advantage of using our solution over a general-purpose cloud storage engine in a distributed network of heterogeneous computing resources.

Description

2012 Fall.
Includes bibliographical references.

Rights Access

Subject

cloud infrastructure
query evaluation
distributed hash tables
distributed file systems
data partitioning

Citation

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