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A distributed polygon retrieval algorithm using MapReduce

Guo, Q and Palanisamy, B and Karimi, HA (2015) A distributed polygon retrieval algorithm using MapReduce. In: UNSPECIFIED.

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Abstract

© 2014 ICST. The proliferation of data acquisition devices like 3D laser scanners had led to the burst of large-scale spatial terrain data which imposes many challenges to spatial data analysis and computation. With the advent of several emerging collaborative cloud technologies, a natural and cost-effective approach to managing such large-scale data is to store and share such datasets in a publicly hosted cloud service and process the data within the cloud itself using modern distributed computing paradigms such as MapReduce. For several key spatial data analysis and computation problems, polygon retrieval is a fundamental operation which is often computed under real-time constraints. However, existing sequential algorithms fail to meet this demand effectively given that terrain data in recent years have witnessed an unprecedented growth in both volume and rate. In this work, we develop a MapReduce-based parallel polygon retrieval algorithm which aims at minimizing the IO and CPU loads of the map and reduce tasks during spatial data processing. The results of the preliminary experiments on a Hadoop cluster demonstrate that the proposed techniques are scalable and lead to more than 35% reduction in execution time of the polygon retrieval operation over existing distributed algorithms.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Guo, Qqig6@pitt.eduQIG6
Palanisamy, Bbpalan@pitt.eduBPALAN
Karimi, HAhkarimi@pitt.eduHKARIMI
Date: 1 January 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: CollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing
Page Range: 435 - 436
Event Type: Conference
DOI or Unique Handle: 10.4108/icst.collaboratecom.2014.257705
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781631900433
Date Deposited: 17 Jun 2015 20:36
Last Modified: 17 Oct 2017 21:55
URI: http://d-scholarship.pitt.edu/id/eprint/25416

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