کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
425092 | 685682 | 2013 | 13 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Exploiting geospatial and chronological characteristics in data streams to enable efficient storage and retrievals Exploiting geospatial and chronological characteristics in data streams to enable efficient storage and retrievals](/preview/png/425092.png)
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.
► Distributed file system designed for storing billions of scientific data files.
► High-throughput storage of geospatial streams.
► Fast retrieval and query support.
► Distributed computation support.
► Visualization capabilities.
Journal: Future Generation Computer Systems - Volume 29, Issue 4, June 2013, Pages 1049–1061