Titan A High-Performance Remote-Sensing Database

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Date
1998-10-15Author
Chang, Chialin
Moon, Bongki
Acharya, Anurag
Shock, Carter
Sussman, Alan
Saltz, Joel
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Show full item recordAbstract
There are two major challenges for a high-performance remote-sensing
database. First, it must provide low-latency retrieval of very large
volumes of spatio-temporal data. This requires effective declustering
and placement of a multi-dimensional dataset onto a large disk
farm. Second, the order of magnitude reduction in data-size due to
post-processing makes it imperative, from a performance perspective,
that the postprocessing be done on the machine that holds the
data. This requires careful coordination of computation and data
retrieval. This paper describes the design, implementation and
evaluation of {\em Titan}, a parallel shared-nothing database designed
for handling remote-sensing data. The computational platform for Titan
is a 16-processor IBM SP-2 with four fast disks attached to each
processor. Titan is currently operational and contains about 24~GB
of data from the Advanced Very High Resolution Radiometer (AVHRR) on the
NOAA-7 satellite. The experimental results show that Titan provides good
performance for global queries, and interactive response times for local
queries.
(Also cross-referenced as UMIACS-TR-96-67)