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A Distributed Polygon Retrieval Algorithm Using MapReduce

Guo, Qiulei and Palanisamy, Balaji and Karimi, Hassan A. (2015) A Distributed Polygon Retrieval Algorithm Using MapReduce. In: The First International Symposium on Spatiotemporal Computing, July 3-15, 2015, Fairfax, VA.

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The burst of large-scale spatial terrain data due to the proliferation of data acquisition devices like 3D laser scanners poses challenges to spatial data analysis and computation. Among many spatial analyses and computations, polygon retrieval is a fundamental operation which is often performed under real-time constraints. However, existing sequential algorithms fail to meet this demand for larger sizes of terrain data. Motivated by the MapReduce programming model, a well-adopted large-scale parallel data processing technique, we present a MapReduce-based polygon retrieval algorithm designed with the objective of reducing the IO and CPU loads of spatial data processing. By indexing the data based on a quad-tree approach, a significant amount of unneeded data is filtered in the filtering stage and it reduces the IO overhead. The indexed data also facilitates querying the relationship between the terrain data and query area in shorter time. The results of the experiments performed in our Hadoop cluster demonstrate that our algorithm performs significantly better than the existing distributed algorithms.


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Item Type: Conference or Workshop Item (Paper)
Status: Published
CreatorsEmailPitt UsernameORCID
Guo, Qiuleiqig6@pitt.eduQIG6
Palanisamy, Balajibpalan@pitt.eduBPALAN
Karimi, Hassan A.hkarimi@pitt.eduHKARIMI
Date: 2015
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Event Title: The First International Symposium on Spatiotemporal Computing
Event Dates: July 3-15, 2015
Event Type: Conference
DOI or Unique Handle: 10.5194/isprsannals-ii-4-w2-51-2015
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Date Deposited: 15 Jun 2016 17:41
Last Modified: 15 Nov 2016 14:33

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