Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Data Management: NetCDF: an Interface for Scientific Data Access
IEEE Computer Graphics and Applications
Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Dryad: distributed data-parallel programs from sequential building blocks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Bigtable: A Distributed Storage System for Structured Data
ACM Transactions on Computer Systems (TOCS)
An Overview of the Granules Runtime for Cloud Computing
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Efficient access to many samall files in a filesystem for grid computing
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science
A demonstration of SciDB: a science-oriented DBMS
Proceedings of the VLDB Endowment
Cassandra: a decentralized structured storage system
ACM SIGOPS Operating Systems Review
Overview of sciDB: large scale array storage, processing and analysis
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Google fusion tables: web-centered data management and collaboration
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
SCC '10 Proceedings of the 2010 IEEE International Conference on Services Computing
The Hadoop Distributed File System
MSST '10 Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)
Analyzing Electroencephalograms Using Cloud Computing Techniques
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Voronoi-Based Geospatial Query Processing with MapReduce
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Hadoop: The Definitive Guide
Galileo: A Framework for Distributed Storage of High-Throughput Data Streams
UCC '11 Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing
Adaptive heterogeneous language support within a cloud runtime
Future Generation Computer Systems
SciMATE: A Novel MapReduce-Like Framework for Multiple Scientific Data Formats
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Autonomous, failure-resilient orchestration of distributed discrete event simulations
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
Autonomously improving query evaluations over multidimensional data in distributed hash tables
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
Polygon-Based Query Evaluation over Geospatial Data Using Distributed Hash Tables
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
| Hi-index | 0.00 |
We describe the design of a high-throughput storage system, Galileo, for data streams generated in observational settings. To cope with data volumes, the shared nothing architecture in Galileo supports incremental assimilation of nodes, while accounting for heterogeneity in their capabilities. 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.