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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
{liut,wangfa,agrawal}@cse.ohio-state.edu
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