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Exploiting Parallelism to Accelerate Keyword Search On Deep-web Sources

Summary: Exploiting Parallelism to Accelerate Keyword
Search On Deep-web Sources
Tantan Liu Fan Wang Gagan Agrawal
Department of Computer Science and Engineering
Ohio State University, Columbus OH 43210
Abstract. Increasingly, biological data is being shared over the deep
web. Many biological queries can only be answered by successively search-
ing a number of distinct web-sites. This paper introduces a system that
exploits parallelization for accelerating search over multiple deep web
data sources. An interactive, two-stage multi-threading system is devel-
oped to achieve task parallelization, thread parallelization, and pipelined
parallelization. We show the effectiveness of our system by considering
a number of queries involving SNP datasets. We show that most of the
queries can be accelerated significantly by exploiting these three forms
of parallelism.
1 Introduction
Biologists today spend large amount of time and effort in querying multiple
remote or local data sources. Integration has become an important phase in bi-
ology research process, as it allows biologists to combine knowledge from multiple


Source: Agrawal, Gagan - Department of Computer Science and Engineering, Ohio State University


Collections: Computer Technologies and Information Sciences