Paper Info
Title
Galileo: A Framework for Distributed Storage of High-Throughput Data Streams
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.
Year
DOI
Venue
2011
10.1109/UCC.2011.13
UCC
Keywords
Field
DocType
high-throughput data streams,query evaluations,distributed storage,high-throughput storage,distributed systems,observational streams,storage management,efficient storage,observational setting,galileo account,data volume,shared-nothing architecture,chronological characteristic,high-throughput storage system,efficient retrieval,data storage,time-series observational data stream,distributed processing,data stream,scale-out architectures,commodity clusters,galileo,geospatial analysis,distributed system,storage system,computer architecture,temperature measurement,indexation,time series,high throughput,indexes
Geospatial analysis,Assimilation (phonology),Galileo (satellite navigation),Data stream mining,Computer science,Computer data storage,Distributed data store,Real-time computing,Storage management,Throughput
Conference
ISBN
Citations 
PageRank 
978-1-4577-2116-8
11
0.60
References 
Authors
13
3
Name
Order
Citations
PageRank
Matthew Malensek19310.44
Sangmi Lee Pallickara217024.46
Shrideep Pallickara383792.72