Galileo: A Framework for Distributed Storage of High-Throughput Data Streams

Authors:
Matthew Malensek;Sangmi Lee Pallickara;Shrideep Pallickara
Affiliations:
-;-;-
Venue:
UCC '11 Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing
Year:
2011

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Expressive Query Support for Multidimensional Data in Distributed Hash Tables

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Exploiting geospatial and chronological characteristics in data streams to enable efficient storage and retrievals

Future Generation Computer Systems
Autonomously improving query evaluations over multidimensional data in distributed hash tables

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Abstract

We describe the design of a high-throughput storage system, Galileo, for data streams generated in observational settings. The shared-nothing architecture in Galileo supports incremental assimilation of nodes, while accounting for heterogeneity in their capabilities, to cope with data volumes. To achieve efficient storage and retrievals of data, Galileo accounts for the geospatial and chronological characteristics of such time-series observational data streams. Our benchmarks demonstrate that Galileo supports high-throughput storage and efficient retrievals of specific portions of large datasets while supporting different types of queries.